Search results for: finite state machine

Authors: Oluwasaanmi Lawrence Adesuyi, Igbekoyi Kayode Emmanuel

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This study examined vote - commercialization during elections among the voters in Nigeria, a series of elections in Ekiti State, Southwestern Nigeria. Democracy in Nigeria that came to replace the unwanted ruling and dictating mission of the military government has been facing a societal terror “crime of votes commercialization” that stands in jeopardy against its sustainability in Nigeria. Social exchange and action-bound theories were employed as the theoretical framework. Forty-Eight in-depth interviews, key informant interviews, and case studies were conducted with purposively selected respondents in the three senatorial districts that captured the sixteen local governments of the state. The results show that really commercialization of votes has become the order of the day in all series of electioneering among Ekiti people. Also, it was recorded that true democracy is no longer allowed to triumph as a result of vote buying that allows the highest bidder to be the winner. The result also shows that this attitude is not limited to only one political party or one candidate but involved all the political parties that participated in Election. It has become a frequent idea among the electorates during every festive period of election in Ekiti State. The tyrannical attitude has been given a nickname to suit the conditional situation of votes commercialization - (Diboki o se obe), which means vote and have a pot of soup, this implies that you will get money to take care of yourself and the family when you vote and collect money on the vote you cast, notwithstanding the money is being collected from all candidates that participated in the election, but the highest bidder has the day. The main challenge this has on democracy is that the contestants challenge the result of the election results based on the act of vote commercialization. Also, those that bought people’s votes with a huge amount of money relent on their democratic promises. The study showed that the crime of vote commercialization that threatens democracy must be addressed for sustainability.

Keywords: crime, democracy, jeopardy, military, sustainability, votes-commercialization

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Authors: Hamidreza Bagheri, Alireza Shariati

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There are many difficulties in the purification of raw components and products. However, researchers are seeking better ways for purification. One of the recent methods is extraction using supercritical fluids. In this study, the phase equilibria of benzoic acid-supercritical carbon dioxide system were investigated. Regarding the phase equilibria of this system, the modeling of solid-supercritical fluid behavior was performed using the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) and Peng-Robinson equations of state (PR EoS). For this purpose, five PC-SAFT EoS parameters for pure benzoic acid were obtained using its experimental vapor pressure. Benzoic acid has association sites and the behavior of the benzoic acid-supercritical fluid system was well-predicted using both equations of state, while the binary interaction parameter values for PR EoS were negative. Genetic algorithm, which is one of the most accurate global optimization algorithms, was also used to optimize the pure benzoic acid parameters and the binary interaction parameters. The AAD% value for the PC-SAFT EoS, were 0.22 for the carbon dioxide-benzoic acid system.

Keywords: supercritical fluids, solubility, solid, PC-SAFT EoS, genetic algorithm

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Authors: Solomon Olusegun Olugbenro

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The purpose of this study is to ascertain the relationship of teachers' personalty and peer pressure on adolescents' personalty in mainland local government, Lagos State, Nigeria. The research design for this study was survey. A representative fraction of the population of mainland local government of lagos was used as sample. One hundred and fifty (150) teenagers whose age ranged from 11-19 from six randomly selected public and private secondary schools in mainland local government area of lagos were used. A four-point likert type questionnaire was constructed for eliciting data for this study. Data were analysed using t-test. The study revealed that there is a significant relationship between teachers' and adolescents' personality development. The study also revealed that there is significant relationship between peer pressure and adolescents' personality development. It was recommended that teachers should be role models to students as they manipulate environmental factors to assist adolescents in their personality development.

Keywords: adolescents, behavior, development, peer pressure, personality, relationship, significant, teachers

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Authors: Hamid Hamli Benzahar

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The main goal of this research is to study the deflection of a composite beam CB taking into account the effect of shear deformation. The structure is made up of two beams of different sections, joined together by thin adhesive, subjected to end moments and a distributed load. The fundamental differential equation of CB can be obtained from the total energy equation while considering the shear deformation. The differential equation found will be compared with those found in CB, where the shear deformation is zero. The CB system is numerically modeled by the finite element method, where the numerical results of deflection will be compared with those found theoretically.

Keywords: composite beam, shear deformation, moments, finites elements

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Authors: Kutub Uddin Chisty, Md. Kamrul Islam, Md. Ashraful Islam

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Growth pattern is an important factor for a city because it can help to predict future growth trend and development of a city. Khagrachari District is one of the three hill tracts districts in Bangladesh. It is bordered by the Indian State of Tripura on the north, Rangamati and Chittagong districts on the south, Rangamati district on the east, Chittagong district and the Indian State of Tripura on the west. Khagrachari Pourashava is surrounded by hills and waterways. The Pourashava area is mostly inhibited by non-tribal population, while tribal population lives in hilly regions within and around the Pourashava area. The hilly area growth is different. Based on questioners and expert opinions survey, growth pattern of Khagrachari is evaluated. Different culture, history, tribal people, non-tribal people enrich the hilly heritages. In our study, we analyse the city growth pattern and identify the prominent factors that influence the city growth. Thus, it can help us to identify growth trend of the city.

Keywords: growth pattern, growth trend, prominent factors, regional development

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Authors: Mohammad Hossein Badamchi

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In Iran as well as other developing countries instituting innovation and entrepreneurship ecosystems by government around the universities is the new imported fashion of modernization and development in the 21st century. In recent decade various statesmen, policy makers, university administrations, economists and development theorists are emphasizing excitingly about the new “start-ups” which are going to solve all economic problems and backwardness of the country. However, critical study of modernization practices in Iran implies that this new trend is suffering from conventional deficiency of modernization planning in 20th century. This article is going to depict the misunderstandings of a situation which we can name “Pseudo-innovation in a closed society” by presenting these 12 paradoxes of this new system, actually happening in Iran: (1) Innovation without freedom? Fiction of innovation in a patriarchal state (2) Entrepreneurship without free market? Fiction of entrepreneurship in a rentier-state. (3) Ecosystem or a state-glasshouse? Is it possible to make and plan an innovation? (4) Innovation; epistemic or practical? How academic innovation could happen abstractly out of context? (5) Risk and Lucre: innovation to protect power and property?! (6) Silicon-valley mirage: what is in common between American-Iranian polity? (7) Information or Communication? ICT startups to restrict the internet (8) The elite paradox: new proletariat of private sector, new governmental clerk or a new path of brain drain? (9) Innovation or commercialization? Revisiting Schumpeterian creative destruction (10) The friendship of Jungle and fire: paradox of public science and market (11) Innovation and revolution: top-down or bottom-up paradox in an Iranian experience (12) Technology instead of civil society: ultimate result of innovation in a closed society. Through explaining these paradoxes we can gradually penetrate the real rationality of Pseudo-innovation ecosystem in a closed society, which can be understood as new-Neopatriarchy reconstruction of traditional patriarchal politics, economy and culture in Iran.

Keywords: innovation, critical sociology, modernisation, Iran, closed society

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Authors: Reem Osama Yousif Ali, Osama Yousif Ali Al Gibali

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Introduction: Balanced nutrition is undeniably essential for maintaining health, body functions, and integrity of cell metabolism; however, some sick patients cannot tolerate oral or enteral feeding to meet their nutritional needs, so partial or total parenteral nutrition (PN) may be the most suitable alternative route in such situations. Dietitians are fundamental personnel among the medical team to ensure the proper provision of PN service, which was introduced in Sudan in the 1980s. Objective: The study aimed to recognize the dietitians' awareness of parenteral nutrition and their role in providing this service in Sudan – Khartoum State. Methodology: Formulated questionnaire forms composed of twelve questions were distributed to the dietitians working in four tertiary level hospitals. Results: The majority (75%) of the responded dietitians had reasonable knowledge about the importance of PN, its advantages, and its indications. Sixty percent of them were mindful of the PN side effects. Most of the dietitians were aware of the different assessment measurements and PN calculations and were exposed in their clinical practice to patients who were in need of PN, but only a few of them (about 30%) had the actual chance to participate in the formulation and application of PN therapy. The unavailability of the multidisciplinary team, lack of the required equipment and financial support, and associated complications were basic obstacles to the provision of long-term PN service in Khartoum state hospitals. Conclusion: Although dietitians in Khartoum state hospitals have good information about PN definition, indications, accesses, and assessment measures, they do not have enough knowledge and clinical exposure that make them confident to provide the PN service. Establishing a few models of parenteral nutrition units in tertiary hospitals will be of great help, as well as providing the dietitian's training in the area of parenteral nutrition. Further study can explore more requirements to run this service.

Keywords: nutrition support, dietitian, Sudan, parenteral nutrition, nutrition support team

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Authors: Synthia A. Sari

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The transparent nomination and selection process is the first step to obtaining qualified members of board. It is believed as the representative (agent) of the owners, members of the board must consist of competent and professional people. However, the development of transparent and ideal nomination and selection process in Indonesian State-owned enterprises (SOEs) has been based on relatively little research. Considering the relative importance attached by boards to conduct their roles in their principal’s interest in a variety of governance tasks in state-owned enterprises, the primary aim of this paper is to shed light on the extent of nomination and selection process impact performance of the board in implementing good corporate governance in Indonesian SOEs. The exploratory nature of this study led to the adoption of a qualitative research methodology which uses semi-structured interviews and publically available documents to collect a range of data pertaining board nomination and selection and the work of boards. Interviews were conducted with four informants from three Indonesian SOEs and Ministry of SOEs. Findings in this study demonstrate unclear job description and expectations board members as a result of unclear functions of the board in Indonesian SOEs make transparent and accountable nomination and selection process hard to conduct. This situation is vulnerable to the influences from political interest and that even the process itself can degenerate into situations of political interference. In the end, it leads to choosing the wrong person for membership of the board. This study makes a significant contribution to several fields; the human resource management, corporate governance, and Southeast studies by addressing the basic research gaps of board selection process issues in Indonesian SOEs. The gap is addressed by providing a more coherent framework for effective nomination and selection system which reflects more clearly the real experiences of those actually involved at board level.

Keywords: board selection and nomination process, Indonesian stated-owned enterprises, good corporate governance, political influence

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Authors: I. O. Oyatayo, K. T. Oyatayo, B. Mamman

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This study was aimed at the assessment of heavy metal pollution of the water in river Benue along Ibi, Taraba State, Nigeria. Water samples were collected at ten sampling points over a distance of 100 meters each. The following water quality parameters were determined: TDS, copper, zinc, chromium, iron, mercury, nickel, and manganese, and the results were compared with the Nigerian Standard for Drinking Water Quality (NSDWQ) and WHO maximum permitted limits. The water quality analysis was conducted using the atomic absorption spectrophotometer (Model: 01-0960-00) at 510 nm. The mean value concentrations of copper, zinc, chromium, nickel, mercury, and mercury are within the permissible limits, while that of iron is above the limit. The summary of ANOVA single-factor statistics with a specified rejection level at α 0.05 is insignificant. The study concludes that the quality of water from river Benue along Ibi is deteriorating and unfit for human consumption. It was recommended that residents of the study area should be enlightened on the effects of indiscriminate dumping of waste and the proper handling and application of fertilizer and herbicides, as some of these end up in the river via surface runoff.

Keywords: heavy, metal, pollution, river, Ibi

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

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Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: O. M. van den Broek

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This article examines how large German companies have responded to the 2014 refugee crisis. It challenges the assumption that the historical legacy of implicit CSR in Germany would lead to low levels of business response through CSR channels. Instead, and building on institutional CSR and the converging forces of globalization, this article argues that the urgency of a humanitarian crisis creates incentives, in the absence of formal institutional arrangement, for explicit CSR responses. This explorative research encompasses the 53 German companies presented on 2015 Forbes2000. A qualitative content analysis of corporate websites was supplemented with inquiry e-mails. Results indicate considerable evidence for the main hypothesis, showing a vast majority of companies responding to the refugee crisis. Levels of engagement varied, depending on the phase of the crisis, from core-business activities to non-integrated action. The high level of partnerships with the state and other non-state actors indicates a quest for enhanced legitimacy in the face of an absent democratic mandate.

Keywords: corporate social responsibility (CSR), implicit versus explicit CSR, public-private partnerships, European refugee crisis

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Authors: Silvia Lorenzo, Hongmian Gong

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With the influx of research assessing the economic impact of the global financial crisis of 2007-8, a spatial analysis based on empirical data is needed to better understand the spatial significance of the financial crisis in New York, a key international financial center also considered the origin of the crisis. Using spatial statistics, the existence of financial clusters specializing in credit and securities throughout the New York metropolitan area are identified for 2000 and 2010, the time period before and after the height of the global financial crisis. Geographically Weighted Regressions are then used to examine processes underlying the formation and movement of financial geographies across state, county and ZIP codes of the New York metropolitan area throughout the 2000s with specific attention to tax regimes, employment, household income, technology, and transportation hubs. This analysis provides useful inputs for financial risk management and public policy initiatives aimed at addressing regional economic sustainability across state boundaries, while also developing the groundwork for further research on a spatial analysis of the global financial crisis.

Keywords: financial clusters, New York, global financial crisis, geographically weighted regression

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Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

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Authors: Mustafa Eruyar, Ersoy Pehlivan, Fatih Kafalı, Fatih Gundogan

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All megacities are not only under the pressure of common urbanization and growth problems but also dealing with different challenges according to their specific circumstances. However, the majority of cities focuses mainly on popular smart city projects, which are usually driven by strong private sector, regardless of their characteristics, each city needs to develop customized projects within a tailor-made smart city roadmap to be able to solve its own challenges. Smart city manifest, helps citizens to feel the action better than good reading smart city vision statements, which consists of five elements; namely purpose, values, mission, vision, and strategy. This study designs a methodology for smart city roadmap based on a top-down approach, breaking down of smart city manifest to feasible projects for a systematic smart city transformation. This methodology was implemented in Istanbul smart city transformation program which includes smart city literature review, current state analysis, roadmap, and architecture projects, respectively. Istanbul smart city roadmap project followed an extensive literature review of certain leading smart cities around the world and benchmarking of the city’s current state using well known smart city indices. In the project, needs of citizens and service providers of the city were identified via stakeholder, persona and social media analysis. The project aimed to develop smart city projects targeting fulfilling related needs by implementing a gap analysis between current state and foreseen plans. As a result, in 11 smart city domains and enablers; 24 strategic objectives, 50 programs, and 101 projects were developed with the support of 183 smart city stakeholder entities and based on 125 citizen persona profiles and last one-year social media analysis. In conclusion, the followed methodology helps cities to identify and prioritize their needs and plan for long-term sustainable development, despite limited resources.

Keywords: needs-based, manifest, roadmap, smart city, top-down approach

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Authors: Michael Ruiz

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Many scholars view the French Revolution as the origins of ‘modern nationalism,’ citing the unprecedented rhetorical power of ‘the nation’ and the emergence of a centralized, modern nation-state during this time. They have also stressed the role of public education in promoting a national language and creating a sense of shared national identity among the masses. Yet as many cultural historians have shown, revolutionary leaders undertook an unprecedented campaign to overhaul French culture in the 1790s in order to cultivate these national ideals and inspire Republican virtues, in what has been called ‘political pedagogy.’ In contrast to scholars of nationalism, who emphasize formal education, revolutionaries attempted to translate abstract ideas of equality and liberty into palpable representations that would inundate everyday life, thereby serving as pedagogical tools. Material culture and everyday life became state apparatuses not just for winning over citizens’ hearts and minds, but for influencing the very formation of the citizen and their innermost ‘self.’ This paper argues that nationalism began in 1789, when ‘the self’ became a political concern and its formation a state project for cultivating political legitimacy. By broadening the meaning of ‘political pedagogy,’ this study brings together scholarship on nationalism with cultural history, thereby highlighting nations and nationalism as banal, palpable, quotidian phenomena and historicizing the complex emergence of ‘modern nationalism.’ Moreover, because the contemporary view of material culture and pedagogy was highly gendered, this study shows the role of culture in the development of a homosocial, male-dominated public sphere in the 19th century. The legacy of the French Revolution’s concern with culture thus persists as much in our vocabulary for political expression as it does in the material world, remaining deeply embedded in everyday day life as a crucial, nearly-invisible, component of nationalism.

Keywords: French Revolution, nationalism, political culture, material culture

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Authors: William Abiodun Duyile

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It is common knowledge that marine food has always been found from the sea, energy can also be found underneath and, to a growing extent; other mineral resources have come from the sea spaces. It is the importance of the sea and the sea lines of communication to littoral nations that has made concepts such as sea power, naval power, etc., significant to them. The study relied on documentary data. The documentary data were sourced from government annual departmental reports, newspapers and correspondence. The secondary sources used were subjected to internal and external criticism for authentication, and then to textual and contextual analyses. The study found that the differential level of seamanship amongst states defined their relationship. It was sea power that gave some states an edge over the others. The study proves that over the ages sea power has been core to the development of States or Empires. The study found that the Nigerian Navy was centre to Nigeria’s conquest of the littoral areas of Biafra, like Bonny, Port-Harcourt, and Calabar; it was also an important turning point of the Nigerian civil war since by it Biafra became landlocked. The research was able to identify succinctly the Nigerian Navy’s contribution to the security and development of the Nigerian State.

Keywords: sea power, naval power, land locked states, warship

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: A. Chatel, I. S. Torreguitart, T. Verstraete

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The paper deals with a single point optimization of the LS89 turbine using an adjoint optimization and defining the design variables within a CAD system. The advantage of including the CAD model in the design system is that higher level constraints can be imposed on the shape, allowing the optimized model or component to be manufactured. However, CAD-based approaches restrict the design space compared to node-based approaches where every node is free to move. In order to preserve a rich design space, we develop a methodology to refine the CAD model during the optimization and to create the best parameterization to use at each time. This study presents a methodology to progressively refine the design space, which combines parametric effectiveness with a differential evolutionary algorithm in order to create an optimal parameterization. In this manuscript, we show that by doing the parameterization at the CAD level, we can impose higher level constraints on the shape, such as the axial chord length, the trailing edge radius and G2 geometric continuity between the suction side and pressure side at the leading edge. Additionally, the adjoint sensitivities are filtered out and only smooth shapes are produced during the optimization process. The use of algorithmic differentiation for the CAD kernel and grid generator allows computing the grid sensitivities to machine accuracy and avoid the limited arithmetic precision and the truncation error of finite differences. Then, the parametric effectiveness is computed to rate the ability of a set of CAD design parameters to produce the design shape change dictated by the adjoint sensitivities. During the optimization process, the design space is progressively enlarged using the knot insertion algorithm which allows introducing new control points whilst preserving the initial shape. The position of the inserted knots is generally assumed. However, this assumption can hinder the creation of better parameterizations that would allow producing more localized shape changes where the adjoint sensitivities dictate. To address this, we propose using a differential evolutionary algorithm to maximize the parametric effectiveness by optimizing the location of the inserted knots. This allows the optimizer to gradually explore larger design spaces and to use an optimal CAD-based parameterization during the course of the optimization. The method is tested on the LS89 turbine cascade and large aerodynamic improvements in the entropy generation are achieved whilst keeping the exit flow angle fixed. The trailing edge and axial chord length, which are kept fixed as manufacturing constraints. The optimization results show that the multilevel optimizations were more efficient than the single level optimization, even though they used the same number of design variables at the end of the multilevel optimizations. Furthermore, the multilevel optimization where the parameterization is created using the optimal knot positions results in a more efficient strategy to reach a better optimum than the multilevel optimization where the position of the knots is arbitrarily assumed.

Keywords: adjoint, CAD, knots, multilevel, optimization, parametric effectiveness

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Authors: Fatimah Opebiyi

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Economic growth promotion, inflation reduction and consumer protection are among the core public interest aims of governments. Nevertheless, higher rates of default by consumers in relation to credit card loans and mortgages in recent times illustrate that government’s performance in balancing the protection of the economy and consumer is subpar. This thereby raises an important question on the role of government in protecting consumers during prolonged spells of inflation, particularly when such inflationary trends may be traceable to the acts of the government. Adopting a doctrinal research methodology, this article investigates the evolution of the concept of consumer protection in the United Kingdom and also brings to the fore the tensions and conflicts of interests in the aims and practices of the main regulators within the financial services industry. Relying on public interest theories of regulation and responsive regulatory theory, the article explores the limitations in the state’s ability to strike the right balance in meeting regulatory aims of the regulatory agencies at the opposite ends of the spectrum.

Keywords: financial regulation, consumer protection, prudential regulation, public interest theories of regulation, central bank

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Authors: Antonio Pizzarello, Oris Friesen

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Networks, such as the electric power grid, must demonstrate exemplary performance and integrity. Integrity depends on the quality of both the system design model and the deployed software. Integrity of the deployed software is key, for both the original versions and the many that occur throughout numerous maintenance activity. Current software engineering technology and practice do not produce adequate integrity. Distributed systems utilize networks where each node is an independent computer system. The connections between them is realized via a network that is normally redundantly connected to guarantee the presence of a path between two nodes in the case of failure of some branch. Furthermore, at each node, there is software which may fail. Self-stabilizing protocols are usually present that recognize failure in the network and perform a repair action that will bring the node back to a correct state. These protocols first introduced by E. W. Dijkstra are currently present in almost all Ethernets. Super stabilization protocols capable of reacting to a change in the network topology due to the removal or addition of a branch in the network are less common but are theoretically defined and available. This paper describes how to use the Software Integrity Assessment (SIA) methodology to analyze self-stabilizing software. SIA is based on the UNITY formalism for parallel and distributed programming, which allows the analysis of code for verifying the progress property p leads-to q that describes the progress of all computations starting in a state satisfying p to a state satisfying q via the execution of one or more system modules. As opposed to demonstrably inadequate test and evaluation methods SIA allows the analysis and verification of any network self-stabilizing software as well as any other software that is designed to recover from failure without external intervention of maintenance personnel. The model to be analyzed is obtained by automatic translation of the system code to a transition system that is based on the use of the weakest precondition.

Keywords: network, power grid, self-stabilization, software integrity assessment, UNITY, weakest precondition

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Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

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Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Michael Sinclair, Andrea Ghermandi, Sheela A. Moses, Joseph Sabu

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Passively crowdsourced data, such as geotagged photographs from social media, represent an opportunistic source of location-based and time-specific behavioral data for ecosystem services analysis. Such data have innovative applications for environmental management and protection, which are replicable at wide spatial scales and in the context of both developed and developing countries. Here we test one such innovation, based on the analysis of the metadata of online geotagged photographs, to investigate the provision of recreational services by the entire network of wetland ecosystems in the state of Kerala, India. We estimate visitation to individual wetlands state-wide and extend, for the first time to a developing region, the emerging application of cultural ecosystem services modelling using data from social media. The impacts of restoration of wetland areal extension and water quality improvement are explored as a means to inform more sustainable management strategies. Findings show that improving water quality to a level suitable for the preservation of wildlife and fisheries could increase annual visits by 350,000, an increase of 13% in wetland visits state-wide, while restoring previously encroached wetland area could result in a 7% increase in annual visits, corresponding to 49,000 visitors, in the Ashtamudi and Vembanad lakes alone, two large coastal Ramsar wetlands in Kerala. We discuss how passive crowdsourcing of social media data has the potential to improve current ecosystem service analyses and environmental management practices also in the context of developing countries.

Keywords: coastal wetlands, cultural ecosystem services, India, passive crowdsourcing, social media, wetland restoration

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Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Fahad Alsharari, Mohd Salmi Md. Noorani

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A Motzkin shift is a mathematical model for constraints on genetic sequences. In terms of the theory of symbolic dynamics, the Motzkin shift is nonsofic, and therefore, we cannot use the Perron-Frobenius theory to calculate its topological entropy. The Motzkin shift M(M,N) which comes from language theory, is defined to be the shift system over an alphabet A that consists of N negative symbols, N positive symbols and M neutral symbols. For an x in the full shift AZ, x is in M(M,N) if and only if every finite block appearing in x has a non-zero reduced form. Therefore, the constraint for x cannot be bounded in length. K. Inoue has shown that the entropy of the Motzkin shift M(M,N) is log(M + N + 1). In this paper, we find a new method of calculating the topological entropy of the Motzkin shift M(M,N) without any measure theoretical discussion.

Keywords: entropy, Motzkin shift, mathematical model, theory

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Authors: Abdu Umar Adamu, Saidu Akun Abdullahi, Al-Hassan Muhammed, Hamisu Abdu

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Leguminous plants such as beans have been considered as a source of protein in this present work. The proximate analysis on beans (Vigna unguiculata) were determined in order to identify the nutritional content as well as presence of some heavy metals accumulation in washed and unwashed beans (white Beans) sold in Kazaure market Jigawa State Nigeria. On the average comparative analysis, the result has indicated that, the Vigna unguiculata had protein content of 61.1%, fibre 4.5%, ash 10.4%, moisture 5%, carbohydrate 15.8% and total lipid 4.9%, therefore it could be suggested that beans has enough nutritional content that helps the people health. The heavy metal analysis of unwashed white beans showed that Fe (17.37 ± 6.71)mg/kg had the highest concentration followed by Zn (6.41 ± 3.09), Cu (5.69 ± 2.42), Cd (0.46 ± 0.65) and Pb (0.57 ± 0.94)mg/kg , while the washed beans shows that Zn (0.11 ± 0.17), Fe (0.01 ± 0.006), Cd (0.02 ± 0.01), Cu (0.03 ± 0.021), Pb (0.01 ± 0.006)mg/kg. The washed white beans are safe for consumption and also the concentration of heavy metal are negligible and of nontoxic effect to human health.

Keywords: white beans, protein, proximate composition, heavy metal

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Authors: Yiling Shao, Megan Dai

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This paper attempts to explore whether the cultural infrastructure supported by the Chinese government is still subject to a logic of “strict regulation”.Previous studies have pointed out that the "paternalism" tendency of China's cultural policy always leads to excessive government intervention in cultural development, while Chinese cultural practitioners can only seek cultural autonomy in the cracks of supervision. This can also explain why Chinese cultural policies sometimes have different effects than the official expectations.But this only reflects one aspect of China's cultural policy. In fact, the welfare cultural infrastructure funded by the government seems to highlight the principles of "safeguarding citizens' cultural rights" and "citizens' voluntary" rather than "indoctrination" and "enlightenment", What new features of China's cultural policy are reflected behind this policy orientation that is completely different from the logic of "regulation", which has also become an important issue in this paper. Based on the field survey of a cultural infrastructure (Gao ming District Cultural Center) in Gao ming District, Fo shan City, Guangdong Province, China, for nearly one year, the authors have obtained many text and picture materials.The paper discusses the dual role of cultural centers in China's cultural policy -both as a formal commitment by the state to protect citizens' basic cultural rights and as a social space for citizens to use preferential policies to obtain cultural capital. All in all, the author have conclued three operational logics of the cultural infrastructure currently supported by the Chinese government (at least in developed areas): first, the cultural center has become a versatile cultural space; second, grass-roots cultural cadres can be described as "policy entrepreneurs"; third, ordinary citizens will use the officially supported cultural infrastructure to increase cultural capital. This paper argues that, in comparison to the common “regulatory hand” in the field of cultural industries, in cultural infrastructure supported by state, the authorities and citizens are not in conflict. On the contrary, authorities must adopt a de-regulatory "pleasing" strategy to gain the support of citizens.

Keywords: cultural infrastructure, cultural capital, deregulation, policy entrepreneur

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Authors: Waqas Ashraf, Yasir Nawab, Haritham Khan, Habib Awais, Shahbaz Ahmad

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Seersucker is a popular lightweight fabric widely used in men’s and women’s suiting, casual wear, children’s clothing, house robes, bed spreads and for spring and summer wear. The puckered effect generates air spaces between body and the fabric, keeping the wearer cool in hot conditions. The aim of this work was to develop knitted seersucker fabric on single cylinder weft knitting machine using plain jersey structure. Core spun cotton yarn and cotton spun yarn of same linear density were used. Core spun cotton yarn, contains cotton fiber in the sheath and elastase filament in the core. The both yarn were fed at regular interval to feeders on the machine. The loop length and yarn tension were kept constant at each feeder. The samples were then scoured and bleached. After wet processing, the fabric samples were washed and tumble dried. Parameters like loop length, stitch density and areal density were measured after conditioning these samples for 24 hours in Standard atmospheric condition. Produced sample has a regular puckering stripe along the width of the fabric with same height. The stitch density of both the flat and puckered area of relaxed fabric was found to be different .Air permeability and moisture management tests were performed. The results indicated that the knitted seersucker fabric has better wicking and moisture management properties as the flat area contact, whereas puckered area held away from the skin. Seersucker effect in knitted fabric was achieved by the difference of contraction of both sets of courses produced from different types of yarns. The seer sucker fabric produce by knitting technique is less expensive as compared to woven seer sucker fabric as there is no need of yarn preparation. The knitted seersucker fabric is more practicable for summer dresses, skirts, blouses, shirts, trousers and shorts.

Keywords: air permeability, knitted structure, moisture management, seersucker

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