Search results for: forest law enforcement

Authors: Jorge R. Santos, Pedro Sebastiao

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In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

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Authors: Corlia van der Walt, Michele K. Havenga

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The study considers corporate governance regulation and practice in South African higher education institutions and makes recommendations for the improvement of current governance practices in this sector. The development of corporate governance principles and practices in South Africa, culminating in the King IV Report on Corporate Governance which was launched in November 2016, is discussed. King IV enjoys international recognition as a progressive corporate governance instrument. It was necessitated by the fundamental changes in business and society nationally and globally, as well as by the significant changes to South African company law introduced by new legislation. Corporate governance and the corporate form are narrowly associated, but there is general recognition that the principles of ethical and effective leadership are not restricted to corporations. Thus King IV was drafted with the express aim that it should apply to all organisations, regardless of their form of incorporation, and the report includes specific sector supplements in support of this aspiration. The South African higher education sector has of late been under intense scrutiny, and a few universities have been placed under administration because of poor governance practices. Universities have also been severely impacted by the consequences of what is generally known as ‘#FeesmustFall’, a student led protest movement initially aimed against the increase of fees at public universities, but which rapidly expanded to also include other concerns. It was clearly necessary to revisit corporate governance policy and practice in the sector. The review of the current higher education governance regime in light of the King IV recommendations, lessons from company law regarding the entrenchment and enforcement of corporate governance principles, and a comparison of higher education governance practices in selected other jurisdictions led to recommendations for the improvement of governance practices in South African higher education. It is further suggested that a sector supplement for higher education institutions may provide additional clarity. Some of the recommendations may be of comparative value for international higher education governance.

Keywords: committees, corporate governance, ethical leadership, higher education institutions, integrated reporting, King IV, sector supplements, sustainability

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

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Authors: William Thomas Worster

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Diplomatic assurances issued by states declaring that they will not mistreat individuals returned to them occupy a strange middle ground between being legal and non-legal obligations. States assert that they are non-binding, yet at other times that they are binding. However, this assertion may not be the end of the discussion. The International Court of Justice and other tribunals have concluded that similar instruments were binding, states have disagreed that certain similar instruments were binding, and the Vienna Convention on the Law of Treaties and its travaux prépératoires do not appear to contemplate non-binding instruments. This paper is a case study of diplomatic assurances but, by necessity, touches on the delicate question of whether certain texts are treaties, promises, or non-binding political statements. International law, and law in general, requires a binary approach to obligation. All communications must be binding or not, even if the fit is not precise. Through this study, we will find that some of the obligations in certain assurances can be understood as legal and some not. We will attempt to state the current methodology for determining which obligations are legal under the law of treaties and law on binding unilateral promises. The paper begins with some background of the legal environment of diplomatic assurances and their use in cases of expulsion. The paper then turns to discuss the legal nature of diplomatic assurances, proceeding to address various possibilities for legal value as treaties and as binding unilateral statements. This paper will not examine the legal value of diplomatic assurances solely under customary international law other than the way in which customary international law might further refine the treaty definition. In order to identify whether any assurances are contained in legal acts, this study identifies a pool of relevant assurances and qualitatively analyzes whether any of those are contained in treaties or binding unilateral statements. To the author’s best knowledge, this study is the first large-scale, qualitative qualitative analysis of assurances as a group of instruments that accounts for their heterogenous nature. It is also the first study to identify the indicators of whether an instrument is a treaty or promise.

Keywords: diplomatic assurances, deportation, extradition, expulsion, non-refoulement, torture, persecution, death penalty, human rights, memorandum of understanding, promises, secret, monitoring, compliance, enforcement

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Authors: Chi-Hsuan Cheng

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This research aims to evaluate public-private partnerships against cyberattacks by comparing the UK and Taiwan. First, the study analyses major cyberattacks and factors influencing cybersecurity in both countries. Second, it assesses the effectiveness of current cyber defence strategies in combating cyberattacks by comparing the approaches taken in the UK and Taiwan, while also evaluating the cyber resilience of both nations. Lastly, the research evaluates existing public-private partnerships by comparing those in the UK and Taiwan, and proposes recommendations for enhancing cooperation and collaboration mechanisms in tackling cyberattacks. Grounded theory serves as the core research method. Theoretical sampling is used to recruit participants in both the UK and Taiwan, including investigators, police officers, and professionals from cybersecurity firms. Semi-structured interviews are conducted in English in the UK and Mandarin in Taiwan, recorded with consent, and pseudonymised for privacy. Data analysis involves open coding, grouping excerpts into codes, and categorising codes. Axial coding connects codes into categories, leading to the development of a codebook. The process continues iteratively until theoretical saturation is reached. Finally, selective coding identifies the core topic, evaluating public-private cooperation against cyberattacks and its implications for social and policing strategies in the UK and Taiwan, which highlights the current status of the cybersecurity industry, governmental plans for cybersecurity, and contributions to cybersecurity from both government sectors and cybersecurity firms, with a particular focus on public-private partnerships. In summary, this research aims to offer practical recommendations to law enforcement, private sectors, and academia for reflecting on current strategies and tailoring future approaches in cybersecurity

Keywords: cybersecurity, cybercrime, public private partnerships, cyberattack

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Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Mueang district, SamutSongkram province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: (1) The identity of Amphur (District) Mueang, SamutSongkram province. This establishment was near the Mouth of Maekong River for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Hoy Lod (Razor Clam) and mangrove trees. Don Hoy Lod, is characterized by muddy beaches, is a coastal wetland for Ramsar Site. It is at 1099th ranging where the greatest number of Hoy Lod (Razor Clam) can be seen from March to May each year. (2) The communication of the identity of AmphurMueang, SamutSongkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of AmphurMueang, SamutSongkram province 2) WatPhetSamutWorrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep AmphurMueang, SamutSongkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

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Authors: Nyasha Agnes Gurira, Petronella Katekwe

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Traditional management systems (TMS) are a vital source of knowledge for conserving cultural and natural heritage. TMS’s are renowned for their ability to preserve both tangible and intangible manifestations of heritage. They are a construct of the intricate relationship that exists between heritage and host communities, where communities are recognized as owners of heritage and so, set up management mechanisms to ensure its adequate conservation. Multiple heritage condition surveys were conducted to assess the effectiveness of using TMS in the conservation of both natural and cultural heritage. Surveys were done at Nharira Hills, Mahwemasimike, Dzimbahwe, Manjowe Rock art sites and Norumedzo forest which are heritage places in Zimbabwe. It assessed the state of conservation of the five case studies and assessed the role that host communities play in the management of these heritage places. It was revealed that TMS’s are effective in the conservation of natural heritage, however in relation to heritage forms with cultural manifestations, there are major disparities. These range from differences in appreciation and perception of value within communities leading to vandalism, over emphasis in the conservation of the intangible element as opposed to the tangible. This leaves the tangible element at risk. Despite these issues, TMS are a reliable knowledge base which enables more holistic conservation approaches for cultural and natural heritage.

Keywords: communities, cultural intangible, tangible heritage, traditional management systems, natural

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Authors: Magigi Wakuru, Gaudensi Kapinga

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This study examines land use changes and its implications on livelihood activities of peri-urban settlements in Msaranga, Moshi Municipality. Specifically; it analyses the historical development of the settlement, socioeconomic characteristics and land use changes over time. Likely, find out existing livelihood activities and how have been changing over time in the context of urbanization, and lastly highlights land use change implications on livelihood activities to residents. Interviews, observations, documentary reviews and mapping were data collection tools employed. The study shows that housing, urban agriculture, roads infrastructure, recreational, open spaces and institutions are some land use types existing in the settlement. On-farm and off-farm livelihood activities have been identified livelihood activities in the settlement. These include crop cultivation, livestock keeping, trading and formal employment and have been changing over time. However, urbanisation observed to be a catalyst of change and affect livelihood activities over time. Resorting to off-farm livelihoods activities including engaging in retail business and seeking employment in formal and informal sector are some copying strategies documented. The study wind up by pointing roles of different actors and issues of particular attention to different stakeholders towards reducing impact of land use changes on livelihood strategies in the settlement. Likely, unresolved issues for future research and policy development agenda are highlighted in this study. The study concludes that the impact of land use changes on livelihood activities need collaborative effort of different stakeholders, policy enforcement as well as public private partnership in issues based implementation in cities like Moshi where land use is rapidly changing over time within urban planning cycles due to increasing population demand in cities of Sub-Saharan Africa.

Keywords: land use, land use changes, livelihood activities, peri-urban settlement, Moshi, Tanzania

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Authors: Sony Subedi, Colleen Davison, Susan Bartels

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Objective: The aim of this study is to i) investigate the socio-demographics and living conditions of households in Haiti pre- and post 2010 earthquake, ii) determine the household prevalence of emotional and physical abuse in children (aged 2-14) after the earthquake, and iii) explore the association between earthquake-related loss and experience of emotional and physical child abuse in the household while considering potential confounding variables and the interactive effects of a number of social, economic, and demographic factors. Methods: A nationally representative sample of Haitian households from the 2005/6 and 2012 phases of the Demographic and Health Surveys (DHS) was used. Descriptive analysis was summarized using frequencies and measures of central tendency. Chi-squared and independent t-tests were used to compare data that was available pre-earthquake and post-earthquake. The association between experiences of earthquake-related loss and emotional and physical child abuse was assessed using log-binomial regression models. Results: Comparing pre-post-earthquake, noteworthy improvements were observed in the educational attainment of the household head (9.1% decrease in “no education” category) and in possession of the following household items: electricity, television, mobile-phone, and radio post-earthquake. Approximately 77.0% of children aged 2-14 experienced at least one form of physical abuse and 78.5% of children experienced at least one form of emotional abuse one month prior to the 2012 survey period. Analysis regarding the third objective (association between experiences of earthquake-related loss and emotional and physical child abuse) is in progress. Conclusions: The extremely high prevalence of emotional and physical child abuse in Haiti indicates an immediate need for improvements in the enforcement of existing policies and interventions aimed at decreasing child abuse in the household.

Keywords: Haiti earthquake, physical abuse, emotional abuse, natural disasters, children

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Authors: Aya Salama

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Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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Authors: Abdelaziz Messis, Azzeddine Bettache, Nawel Boucherba, Said Benallaoua, Mouloud Kecha

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Actinobacteria are of special biotechnological interest since they are known to produce chemically diverse compounds with a wide range of biological activity. This distinct clade of Gram-positve bacteria include some of the key antibiotic producers and are also sources of several bioactive compounds, established commercially a newly filamentous bacteria was recovered from Tikjda forest soil (Algeria) for its high antifungal activity against various pathogenic and phytopathogenic fungi. The nucleotide sequence of the 16S rRNA gene (1454 pb) of Streptomyces sp. TKJ2 exhibited close similarity (99 %) with other Streptomyces16S rRNA genes. Antifungal metabolite production of Streptomyces sp TKJ2 was evaluated using six different fermentation media. The extracellular products contained potent antifungal agents. Antifungal protein produced by Streptomyces sp. TKJ2 on PCA medium has been purified by ammonium sulfate precipitation, SPE column chromatography and high-performance liquid chromatography in a reverse-phase column. The UV chromatograms of the active fractions obtained at 214 nm by NanoLC-ESI-MS/MS have different molecular weights. The F20 Peptidic fraction obtained from culture filtrat of Streptomyces sp. TKJ2 precipitated at 30% of ammonium sulfate was selected for analysis by infusion ESI-MS which yielded a singly charged ion mass of 437.17 Da.

Keywords: actinobacteria, antifungal protein, chromatography, Streptomyces

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Authors: Herbert Ntuli, Edwin Muchapondwa

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This study used a sample of 336 households and community level data from 30 communities around the Gonarezhou National Park in Zimbabwe to analyse the association between ability to self-organize or cooperation and institutions on one hand and the relationship between success of biodiversity outcomes and cooperation on the other hand. Using both the ordinary least squares and instrumental variables estimation with heteroskedasticity-based instruments, our results confirmed that sound institutions are indeed an important ingredient for cooperation in the respective communities and cooperation positively and significantly affects biodiversity outcomes. Group size, community level trust, the number of stakeholders and punishment were found to be important variables explaining cooperation. From a policy perspective, our results show that external enforcement of rules and regulations does not necessarily translate into sound ecological outcomes but better outcomes are attainable when punishment is rather endogenized by local communities. This seems to suggest that communities should rather be supported in such a way that robust institutions that are tailor made to suit the needs of local condition will emerge that will in turn facilitate good environmental husbandry. Cooperation, training, benefits, distance from the nearest urban canter, distance from the fence, social capital average age of household head, fence and information sharing were found to be very important variables explaining the success of biodiversity outcomes ceteris paribus. Government programmes should target capacity building in terms of institutional capacity and skills development in order to have a positive impact on biodiversity. Hence, the role of stakeholders (e.g., NGOs) in capacity building and government effort should complement each other to ensure that the necessary resources are mobilized and all communities receive the necessary training and resources.

Keywords: institutions, self-organize, common pool resources, wildlife, conservation, Zimbabwe

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Menouni Aziza, Chbihi Kaoutar, El Jaafari Samir

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There is strong evidence connecting epidemics with the disruption of the human-animal-environment interaction. Despite the fact that several cases of emerging and endemic zoonotic diseases indifferent parts of Africa have been documented, there is limited data regarding which specific interventions are effective in preventing and managing the associated risks using a One Health approach. The aim of this study is to better understand perceptions and ongoing research related to interventions in Africa through the implementation of suitable projects and policies. A bibliometric review of the scientific literature on one health studies with a focus on African countries was conducted, followed by a qualitative survey among stakeholders involved in fields related to One Health research or management in the Africa, including veterinary experts, public health professionals, environmentalists and policy makers, to learn about determinants of their perceptions, as well as barriers to and promoters of successful interventions and governance. The project was concluded with an international workshop in March 2023, where a broad range of topics relevant to One Health were discussed. 94% of the respondents were aware of the importance of the One Health approach and strongly endorse it within their respective countries. The top reported barriers to One Health development in Africa included paucity of data, weak linkages and institutional communication between the different departments and the lack of funding. Key areas of improvement identified were the impact evaluation of current initiatives, awareness raising campaigns among citizens targeted at behavioral changes, capacity building of relevant professionals and stakeholders, as well as the implementation of adequate policies and enforcement of national and continental regulations, allowing for better coordination on the African level. All One Health sectors in Africa require strong governance and leadership, as well as inter-ministerial, inter-sectoral, and interdisciplinary cooperation.

Keywords: one health, perceptions, governance, Africa

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Authors: Somia Lakehal Ayat, Ibtissem Samai, Srara Lakehal Ayat, Chaima Dahmani

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The aim of this work relates to the physicochemical diversity and the characterization of the different types of soils of the edough massif (North East of Algeria) and to the evaluation and characterization of the existing organic matter as well as to the evolution. and the dynamics of the latter, also on its influence on changes in the physical properties of soils. In order to know the soil properties of seraidi forest, we established a stratified sampling plan. The results obtained show that we are in the presence of a great diversity of soils, such as neutral to alkaline, whose adsorbent complex is sufficiently saturated. Also, the presence of limestone offers the soil a fairly significant buffering capacity. In our study region, the texture of the soils is varied between clayey and silty, where it offers medium porosity, there is a strong accumulation of organic matter, therefore soils rich in organic matter.The fractionation of the organic matter of the soils allowed to obtain a very high rate of humification. The soil characteristics of the edough massif (North East of Algeria) are controlled by the contribution of organic matter, which presents a dynamic and an important evolution and which varies with the climatic conditions and the nature and the type of plant formation, and these the latter have a capital and important role in the rate of mineralization of organic matter.

Keywords: organic matter, soil, foresty, diversity, mineralization

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Authors: Sara Vora (Hoxha)

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Defamation, invasion of privacy, and cyberbullying have all increased in tandem with the growth of the internet. European international private law may struggle to deal with such transgressions if they occur in many jurisdictions. The current study examines how effectively the legal system of European international private law addresses abuses of personality rights in cyberspace. The study starts by discussing how established legal frameworks are being threatened by online personality rights abuses. The article then looks into the rules and regulations of European international private law that are in place to handle overseas lawsuits. This article examines the different elements that courts evaluate when deciding which law to use in a particular case, focusing on the concepts of jurisdiction, choice of law, and recognition and execution of foreign judgements. Next, the research analyses the function of the European Union in preventing and punishing online personality rights abuses. Key pieces of law that control the collecting and processing of personal data on the Internet, including the General Data Protection Regulation (GDPR) and the e-Commerce Directive, are discussed. In addition, this article investigates how the ECtHR handles cases involving the infringement of personal freedoms, including privacy and speech. The article finishes with an assessment of how well the legal framework of European international private law protects individuals' right to privacy online. It draws attention to problems with the present legal structure, such as the inability to enforce international judgements, the inconsistency between national laws, and the necessity for stronger measures to safeguard people' rights online. This paper concludes that while European international private law provides a useful framework for dealing with violations of personality rights online, further harmonisation and stronger enforcement mechanisms are necessary to effectively protect individuals' rights in the digital age.

Keywords: European international private law, personality rights, internet, jurisdiction, cross-border disputes, data protection

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Authors: Katawut Kaewbanjong

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We analyzed a volume of data and found significant user satisfaction in software project factors. A statistical significance analysis (logistic regression) and collinearity analysis determined the significance factors from a group of 71 pre-defined factors from 191 software projects in ISBSG Release 12. The eight prediction models used for testing the prediction potential of these factors were Neural network, k-NN, Naïve Bayes, Random forest, Decision tree, Gradient boosted tree, linear regression and logistic regression prediction model. Fifteen pre-defined factors were truly significant in predicting user satisfaction, and they provided 82.71% prediction accuracy when used with a neural network prediction model. These factors were client-server, personnel changes, total defects delivered, project inactive time, industry sector, application type, development type, how methodology was acquired, development techniques, decision making process, intended market, size estimate approach, size estimate method, cost recording method, and effort estimate method. These findings may benefit software development managers considerably.

Keywords: prediction model, statistical analysis, software project, user satisfaction factor

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Authors: Samuel Emeka Anarah, Kingsley Nnaemeka Ogbu, Obasi Arinze

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Quantifying the hydrological response due to changes in climate change is imperative for proper management of water resources within a watershed. The impact of climate change on the hydrology of the Upper Ebony River (UER) watershed, South East Nigeria, was studied using the Soil and Water Assessment Tool (SWAT) hydrological model. A climatological time series analysis from 1985 - 2014 using non-parametric test showed significant negative trends in precipitation and relative humidity trend while minimum and maximum temperature, solar radiation and wind speed showed significant positive trends. Future hypothetical land-use change scenarios (Scenarios 1, 2, 3 and 4) representing urbanization and conversion of forest to agricultural land were combined with future downscaled climate model (CSIRO-Mk3-6-0) and simulated in SWAT model. Relative to the Baseline scenario (2005 - 2014), the results showed a decrease in streamflow by 10.29%, 26.20%, 11.80% and 26.72% for Scenarios 1, 2, 3, and 4 respectively. Model results suggest development of adaptation strategies to cope with the predicted hydrological conditions under future climate change in the watershed.

Keywords: climate change, hydrology, runoff, SWAT model

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Authors: Collins Ogbu, Godwin Johnny Akpan, James NDA Jacob

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The debilitating outcomes of violent conflict, consummated by rural armed banditry have nonetheless, occasioned the need for the mapping of crime zones in Nigeria. As a step towards understanding the scourge of armed bandits, ungoverned spaces have been uncovered as the most dominant excuse for rural crimes and fierce confrontations. From the creeks of the Niger Delta to the forest of Sambisa, Small Arms and Light Weapons (SALW) have proliferated to the vagaries of national insecurity. While the trends present indications of State fragility, the paucity of governance in these so-called ungoverned spaces has persistently reflected a Hobbesian state of nature, where the fittest survives. This study, therefore, interrogates the demographic implications of these ungoverned spaces by specifically identifying the most immediate features of the characters in the areas under investigation. The Farmers-Herders Crises, Niger-Delta Militancy, Boko-Haram Insurgency, Armed Robbery, Kidnapping and Cattle Rustling all define the major focus. In undertaking this study, anecdotal sources will be relied on, while extant information on the concept of ungoverned spaces will be content-analyzed. It is hoped that the knowledge gathered, as a result, will ultimately aid in proffering a dependable panacea to the crises of rural armed banditry in Nigeria.

Keywords: ungoverned spaces, rural armed banditry, state fragility, conflicts

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Authors: Sónia Ribeiro, Diana Farinha, Hélia Sales, Rita Pontes, João Nunes

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The demand and commitment to sustainability in the agrifood sector introduce news opportunities for new composite materials. Composite materials are emerging as a vital entity for the sustainable development. Polylactic acid (PLA) has been recognized as a potential polymer with attractive characteristics for agrifood sector applications. PLA that can be beneficial for the development of composites, biocomposites, films, porous gels, and so on. The production of PLA from lignocellulosic biomass residues matrix is a key option towards a sustainable and circular bioeconomy and a non-competitive application with feed and food sector. The Flui and BeirInov projects presents news developments in the production of PLA composites to value the Portuguese forest ecosystem, with high amount of lignocellulosic biomass residues and available. A performance production of lactic acid from lignocellulosic biomass undergoes a process of autohydrolysis, saccharification and fermentation, originating a lactic acid fermentation medium with a 72.27g.L-1 was obtained and a final purification of 72%. The high purification PLA from multi lignocellulosic residues representing one economic expensive process, and a new materials and application for the polymers and a combination with others types of composites matrix characteristic is the drive-up for this green market.

Keywords: polylactic acid, lignocellulosic biomass, agrifood, composite materials

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Authors: Victoria Masi Haruna Karatu, Nik Kamariah Nikmat

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In recent times awareness about the environment and green purchase has been on the increase across nations due to global warming. Previous researchers have attempted to determine what actually influences the purchase intention of consumers in this environmentally conscious epoch. The consumers too have become conscious of what to buy and who to buy from in their purchasing decisions as this action will reflect their concern about the environment and their personal well-being. This trend is a widespread phenomenon in most developed countries of the world. On the contrary evidence revealed that only 5% of the populations of Nigeria involve in green purchase activities thus making the country lag behind its counterparts in green practices. This is not a surprise as Nigeria is facing problems of inadequate green knowledge, non-enforcement of environmental regulations, sensitivity to the price of green products when compared with the conventional ones and distrust towards green products which has been deduced from prior studies of other regions. The main objectives of this study is to examine the direct antecedents of green purchase intention (green availability, government regulations, perceived green knowledge, perceived value and green price sensitivity) in Nigeria and secondly to establish the mediating role of perceived behavioral control on the relationship between these antecedents and green purchase intention. The study adopts quantitative method whereby 700 questionnaires were administered to lecturers in three Nigerian universities. 502 datasets were collected which represents 72 percent response rate. After screening the data only 440 were usable and analyzed using structural equation modeling (SEM) and bootstrapping. From the findings, three antecedents have significant direct relationships with green purchase intention (perceived green knowledge, perceived behavioral control, and green availability) while two antecedents have positive and significant direct relationship with perceived behavioral control (perceived value and green price sensitivity). On the other hand, PBC does not mediate any of the paths from the predictors to criterion variable. This result is discussed in the Nigerian context.

Keywords: Green Availability, Green Price Sensitivity, Green Purchase Intention, Perceived Green Knowledge, Perceived Value

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Authors: Olufunke Ayilara Aje-Famuyide

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The centrality of the Petroleum Industry in the world energy is undoubted. The world economy almost runs and depends on petroleum. Petroleum industry is a multi-trillion industry; it turns otherwise poor and underdeveloped countries into wealthy nations and thrusts them at the center of international diplomacy. Although these developing nations lack the necessary technology to explore and exploit petroleum resources they are not without help as developed nations, represented by their multinational corporations are ready and willing to provide both the technical and managerial expertise necessary for the development of this natural resource. However, the exploration of these petroleum resources comes with, sometimes, grave, concomitant consequences. These consequences are especially pronounced with respect to the environment. From the British Petroleum Oil rig explosion and the resultant oil spillage and pollution in New Mexico, United States to the Mobil Oil spillage along Nigerian coast, the story and consequence is virtually the same. Nigeria’s Niger Delta Region produces Nigeria’s petroleum which accounts for more than ninety-five percent of Nigeria’s foreign exchange earnings. Between 1999 and 2007, Nigeria earned more than $400 billion from petroleum exports. Nevertheless, petroleum exploration and exploitation has devastated the Niger Delta environment. From oil spillage which pollutes the rivers, farms and wetlands to gas flaring by the multi-national corporations; the consequences is similar-a region that has been devastated by petroleum exploitation. This paper thus seeks to examine the consequences and impact of petroleum pollution in the Niger Delta of Nigeria with particular reference on the right of the people of Niger Delta to a healthy environment. The paper further seeks to examine the relevant international, regional instrument and Nigeria’s municipal laws that are meant to protect the result of the people of the Niger Delta and their enforcement by the Nigerian State. It is quite worrisome that the Niger Delta Region and its people have suffered and are still suffering grave violations of their right to a healthy environment as a result of petroleum exploitation in their region. The Nigerian effort at best is half-hearted in its protection of the people’s right.

Keywords: environment, exploration, petroleum, pollution

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Authors: Francisca Margarita Ocran

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Underwear, and more particularly bras and panties, are defined as intimate clothing. Strictly speaking, they enhance the place of women in the public or private satchel. Therefore, women's lingerie is a complex garment with a high involvement profile, motivating consumers to buy it not only by its functional utility but also by the multisensory experience it provides them. Customer behavior models are generally based on customer data mining, and each model is designed to answer questions at a specific time. Predicting the customer experience is uncertain and difficult. Thus, knowledge of consumers' tastes in lingerie deserves to be treated as an experiential product, where the dimensions of the experience motivating consumers to buy a lingerie product and to remain faithful to it must be analyzed in detail by the manufacturers and retailers to engage and retain consumers, which is why this research aims to identify the variables that push consumers to choose their lingerie product, based on an in-depth analysis of the types of fabrics used to make lingerie. The data used in this study comes from online purchases. Machine learning approach with the use of Python programming language and Pycaret gives us a precision of 86.34%, 85.98%, and 84.55% for the three algorithms to use concerning the preference of a buyer in front of a range of lingerie. Gradient Boosting, random forest, and K Neighbors were used in this study; they are very promising and rich in the classification of preference in the textile industry.

Keywords: consumer behavior, data mining, lingerie, machine learning, preference

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Authors: Tanmay Bisen, Aastha Shayla

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This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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Authors: J. Zekri, N. Souilah, W. Abdelaziz, D. Alatou

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Our study shall focus on the ability of trees cork oak that showed vis-à-vis sensitivity to climate change, including late spring frosts. The combination of these factors resulted in damage alarmed, therefore forest ecosystems weakened trees that can affect their ability to support other abiotic and biotic stresses, For this we tested its tolerance to thermal variations and cold weather conditions by estimating some stress markers (quantification of proteins, RNA, soluble sugars) that are quantified to evaluate the cold tolerance of seedlings. Sowing of cork oak (Quercus suber L.) is grown in controlled conditions at 25° C ± 2° C in long days 16h. These seedlings are transferred at low temperatures between 5° C and -6° C for a period of 3 hours. Biochemical analyzes were performed in the various organs of the cork oak seedlings. Cool temperatures induced a significant accumulation of proline in different organs of seedlings and the optimum concentrations were observed in the roots with very high concentrations (4 times larger than those of the control). The accumulation of soluble sugars is significantly in stems and roots at 0° C. Protein concentrations are very high in leaves of both growth and high waves in rod at -4° C to -2° C. Tolerance cork oak seems to be at the thermal limit of -2°C. The concentration of these metabolites in the various organs showed the ability oak cork hardening during the winter.

Keywords: climate change, thermal change, semi-aride, biochemical markers, heat stress

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Authors: Victoria L. Chester, Usha Kuruganti

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The forest industry is a major economic sector of Canada and also one of the most dangerous industries for workers. The use of mechanized mobile forestry harvesting machines has successfully reduced the incidence of injuries in forest workers related to manual labor. However, these machines have also created additional concerns, including a high machine operation learning curve, increased the length of the workday, repetitive strain injury, cognitive load, physical and mental fatigue, and increased postural loads due to sitting in a confined space. It is critical to obtain objective performance data for employers to develop appropriate work practices for this industry, however ergonomic field studies of this industry are lacking mainly due to the difficulties in obtaining comprehensive data while operators are cutting trees in the woods. The purpose of this study was to establish a measurement and experimental protocol to examine the effects of worker skill level and movement training speed (joystick crane speed) on harvesting performance using a forestry simulator. A custom wrist angle measurement device was developed as part of the study to monitor Euler angles during operation of the simulator. The device of the system consisted of two accelerometers, a Bluetooth module, three 3V coin cells, a microcontroller, a voltage regulator and an application software. Harvesting performance and crane data was provided by the simulator software and included tree to frame collisions, crane to tree collisions, boom tip distance, number of trees cut, etc. A pilot study of 3 operators with various skill levels was tested to identify factors that distinguish highly skilled operators from novice or intermediate operators. Dependent variables such as reaction time, math skill, past work experience, training movement speed (e.g. joystick control speeds), harvesting experience level, muscle activity, and wrist biomechanics were measured and analyzed. A 10-channel wireless surface EMG system was used to monitor the amplitude and mean frequency of 10 upper extremity muscles during pre and postperformance on the forestry harvest stimulator. The results of the pilot study showed inconsistent changes in median frequency pre-and postoperation, but there was the increase in the activity of the flexor carpi radialis, anterior deltoid and upper trapezius of both arms. The wrist sensor results indicated that wrist supination and pronation occurred more than flexion and extension with radial-ulnar rotation demonstrating the least movement. Overall, wrist angular motion increased as the crane speed increased from slow to fast. Further data collection is needed and will help industry partners determine those factors that separate skill levels of operators, identify optimal training speeds, and determine the length of training required to bring new operators to an efficient skill level effectively. In addition to effective and employment training programs, results of this work will be used for selective employee recruitment strategies to improve employee retention after training. Further, improved training procedures and knowledge of the physical and mental demands on workers will lead to highly trained and efficient personnel, reduced risk of injury, and optimal work protocols.

Keywords: EMG, forestry, human factors, wrist biomechanics

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 192

Authors: Shidratul Moontaha Suha

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Violence is organized and utilized differently in various communities across the globe. The capacity to employ violence in numerous societies is largely limited to the apparatus of the state, like law enforcement officers, and in a small share of contexts, it is controlled within the state institutions as per the rule of law. Contrastingly, in many other societies, a broad array of players, mainly organized criminal gangs, are using violence on a substantial scale to agitate against social ills or attain personal interests. The present paper examined the role of social injustice in driving children living off and on the streets of Dhaka, Bangladesh, into joining organized criminal gangs and committing crimes. The study entailed a comprehensive review of existing literature with theoretical analyses based on three theories: the Marxist’s theory of capitalism and class struggle, the Weberian model of social stratification theory, and the social disorganization theory. The analysis revealed that, in Dhaka, Bangladesh, criminal gangs emerged from social disorganization of communities characterized by absolute poverty, residential mobility, and population heterogeneity, which promote deviance among the youth, and subsequently, led to the rise of organized gangs and delinquency. Although the latter was formed as a response to class struggle, they have been employed by the state and police as the tools of exploitation and oppression to rule the working class. The criminal gangs exploit the vulnerability of street children by using them as sources of cheap labor to peddle drugs, extort, or kill specific individuals who are against their ideals. In retrospect, the street children receive individual, group, and social protection. Therefore, social class struggle plays a central role in the proliferation of organized criminal gangs and the engagement of street children in criminal activities in Dhaka, Bangladesh.

Keywords: cheap labor, organized crimes, poverty, social stratification, social children

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Authors: Matthew Venunye Fianu, Jerry Fiave, Ebenezer Kye-Mensah, Dacosta Aboagye, Felix Osei-Sarpong

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Introduction: Road traffic accidents involving motorbikes are a priority public health concern in Ghana. While there are local initiatives to address this public health challenge, little is known about motor riders’ knowledge and compliance with road safety regulations (RSR) and their association with RTAs. The aim of this study was, therefore, to assess motorbike riders’ knowledge and compliance with RSRs. Methodology: Motorbike riders in Hohoe Municipality were randomly sampled in a cross-sectional study in June 2022. Data were collected from 237 riders using a questionnaire designed in Kobocollect and administered by ten research assistants. A score of 70% or less is considered low for knowledge and compliance. The data were exported into Excel and imported into STATA 17 for analysis. A chi-square test was performed to generate descriptive and inferential statistics to establish the association between independent and dependent variables. Results: All 237 respondents were male, and each of them completed the questionnaire representing a 100% response rate. Participants who had knowledge about speed limit at different segments of the road were 59(24.9%), the use of helmet were 124 (52.3%), and alcohol use were 152 (64.1%). Participants who complied with regulations on speed limits, helmet use, and alcohol use were 108 (45.6%), 179(75.5%), and 168(70.8%), respectively. Riders who had at least junior high school education were 2.43 times more likely to adhere to RSR [cOR =2.43(95%CI= 1.15-6.33) p= 0.023] than those who had less education. Similarly, riders who had high knowledge about RSR were 2.07 times more likely to comply with RSR than those who had less knowledge [AOR= -2.07 (95% CI= 0.34-0.97), p=0.038]. Conclusion: Motor riders in the Hohoe Municipality had low knowledge as well as low compliance with road safety regulations. This could be a contributor to road traffic accidents. It is therefore recommended that road safety regulatory authorities and relevant stakeholders enhance the enforcement of RSR. There should also be country-specific efforts to increase awareness among all motor riders, especially those with less than junior high school education.

Keywords: compliance, motor riders, road safety regulations, road traffic accident

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Authors: Osayande Pascal Omondiagbe, Sherlock a Licorish

Abstract:

Stack Overflow is a popular community question and answer portal which is used by practitioners to solve technology-related challenges during software development. Previous studies have shown that this forum is becoming a substitute for official software programming languages documentation. While tools have looked to aid developers by presenting interfaces to explore Stack Overflow, developers often face challenges searching through many possible answers to their questions, and this extends the development time. To this end, researchers have provided ways of predicting acceptable Stack Overflow answers by using various modeling techniques. However, less interest is dedicated to examining the performance and quality of typically used modeling methods, and especially in relation to models’ and features’ complexity. Such insights could be of practical significance to the many practitioners that use Stack Overflow. This study examines the performance and quality of various modeling methods that are used for predicting acceptable answers on Stack Overflow, drawn from 2014, 2015 and 2016. Our findings reveal significant differences in models’ performance and quality given the type of features and complexity of models used. Researchers examining classifiers’ performance and quality and features’ complexity may leverage these findings in selecting suitable techniques when developing prediction models.

Keywords: feature selection, modeling and prediction, neural network, random forest, stack overflow

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