Search results for: fork split trees

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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Authors: Linda D. F. Bambara, Marie Sawadogo

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Jatropha curcas (jatropha) is the plant that has been the most studied for biofuel production in West Africa. There exist however other plants such as Balanites aegyptiaca (balanites) that have been targeted as a potential feedstock for biofuel production. This biomass could be an alternative feedstock for the production of straight vegetable oil (SVO) at costs lower than jatropha-based SVO production costs. This study aims firstly to determine, through an MILP model, the optimal organization that minimizes the costs of the oilseeds supply of two biomass conversion units (BCU) exploiting respectively jatropha seeds and the balanitès seeds. Secondly, the study aims to carry out a comparative study of these costs obtained for each BCU. The model was then implemented on two theoretical cases studies built on the basis of the common practices in Burkina Faso and two scenarios were carried out for each case study. In Scenario 1, 3 pre-processing locations ("at the harvesting area", "at the gathering points", "at the BCU") are possible. In scenario 2, only one location ("at the BCU") is possible. For each biomass, the system studied is the upstream supply chain (harvesting, transport and pre-processing (drying, dehulling, depulping)), including cultivation (for jatropha). The model optimizes the area of land to be exploited based on the productivity of the studied plants and material losses that may occur during the harvesting and the supply of the BCU. It then defines the configuration of the logistics network allowing an optimal supply of the BCU taking into account the most common means of transport in West African rural areas. For the two scenarios, the results of the implementation showed that the total area exploited for balanites (1807 ha) is 4.7 times greater than the total area exploited for Jatropha (381 ha). In both case studies, the location of pre-processing “at the harvesting area” was always chosen for scenario1. As the balanites trees were not planted and because the first harvest of the jatropha seeds took place 4 years after planting, the cost price of the seeds at the BCU without the pre-processing costs was about 430 XOF/kg. This cost is 3 times higher than the balanites's one, which is 140 XOF/kg. After the first year of harvest, i.e. 5 years after planting, and assuming that the yield remains constant, the same cost price is about 200 XOF/kg for Jatropha. This cost is still 1.4 times greater than the balanites's one. The transport cost of the balanites seeds is about 120 XOF/kg. This cost is similar for the jatropha seeds. However, when the pre-processing is located at the BCU, i.e. for scenario2, the transport costs of the balanites seeds is 1200 XOF/kg. These costs are 6 times greater than the transport costs of jatropha which is 200 XOF/kg. These results show that the cost price of the balanites seeds at the BCU can be competitive compared to the jatropha's one if the pre-processing is located at the harvesting area.

Keywords: Balanites aegyptiaca, biomass conversion, Jatropha curcas, optimization, post-harvest operations

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Authors: Robert Birkholc

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One of the basic issues related to the creation of characters in media, such as literature and film, is the representation of the characters' thoughts, emotions, and perceptions. This paper is devoted to the social perspective (or the focalization) expressed in film narration. The aim of the paper is to show how social point of view of the hero –conditioned by his origin and the environment from which he comes– can be created by using non-verbal, purely audiovisual means of expression. The issue will be considered on the example of the little-known polish movie The Dancing Hawk (1977) by Grzegorz Królikiewicz, based on the novel by Julian Kawalec. The thesis of the paper is that the polish director uses a narrative figure, which is somewhat analogous to literary form of free indirect discourse. In literature, free indirect discourse is formally ‘spoken’ by the external narrator, but the narration is clearly filtered through the language and thoughts of the character. According to some scholars (such as Roy Pascal), the narrator in this form of speech does not cite the character's words, but uses his way of thinking and imitates his perspective – sometimes with a deep irony. Free indirect discourse is frequently used in Julian Kawalec’s novel. Through the linguistic stylization, the author tries to convey the socially determined perspective of a peasant who migrates to the big city after the Second World War. Grzegorz Królikiewicz expresses the same social experience by pure cinematic form in the adaptation of the book. Both Kawalec and Królikiewicz show the consequences of so-called ‘social advancement’ in Poland after 1945, when the communist party took over political power. On the example of the fate of the main character, Michał Toporny, the director presents the experience of peasants who left their villages and had to adapt to new, urban space. However, the paper is not focused on the historical topic itself, but on the audiovisual form of the movie. Although Królikiewicz doesn’t use frequently POV shots, the narration of The Dancing Hawk is filtered through the sensations of the main character, who feels uprooted and alienated in the new social space. The director captures the hero's feelings through very complex audiovisual procedures – high or low points of view (representing the ‘social position’), grotesque soundtrack, expressionist scenery, and associative editing. In this way, he manages to create the world from the perspective of a socially maladjusted and internally split subject. The Dancing Hawk is a successful attempt to adapt the subjective narration of the book to the ‘language’ of the cinema. Mieke Bal’s notion of focalization helps to describe ‘free indirect discourse’ as a transmedial figure of representing of the characters’ perceptions. However, the polysemiotic medium of the film also significantly transforms this figure of representation. The paper shows both the similarities and differences between literary and cinematic ‘free indirect discourse.’

Keywords: film and literature, free indirect discourse, social experience, subjective narration

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Authors: Charlotte Entwistle, Ryan Boyd

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Recent developments in information retrieval techniques and natural language processing have allowed for greater exploration of psychological and social processes. Linguistic analysis methods for understanding behaviour have provided useful insights within the field of mental health. One area within mental health that has received little attention though, is borderline personality disorder (BPD). BPD is a common mental health disorder characterised by instability of interpersonal relationships, self-image and affect. It also manifests through maladaptive behaviours, such as impulsivity and self-harm. Examination of language patterns associated with BPD could allow for a greater understanding of the disorder and its links to maladaptive thoughts and behaviours. Language analysis methods could also be used in a predictive way, such as by identifying indicators of BPD or predicting maladaptive thoughts, emotions and behaviours. Additionally, associations that are uncovered between language and maladaptive thoughts and behaviours could then be applied at a more general level. This study explores linguistic characteristics of BPD, and their links to maladaptive thoughts and behaviours, through the analysis of social media data. Data were collected from a large corpus of posts from the publicly available social media platform Reddit, namely, from the ‘r/BPD’ subreddit whereby people identify as having BPD. Data were collected using the Python Reddit API Wrapper and included all users which had posted within the BPD subreddit. All posts were manually inspected to ensure that they were not posted by someone who clearly did not have BPD, such as people posting about a loved one with BPD. These users were then tracked across all other subreddits of which they had posted in and data from these subreddits were also collected. Additionally, data were collected from a random control group of Reddit users. Disorder-relevant behaviours, such as self-harming or aggression-related behaviours, outlined within Reddit posts were coded to by expert raters. All posts and comments were aggregated by user and split by subreddit. Language data were then analysed using the Linguistic Inquiry and Word Count (LIWC) 2015 software. LIWC is a text analysis program that identifies and categorises words based on linguistic and paralinguistic dimensions, psychological constructs and personal concern categories. Statistical analyses of linguistic features could then be conducted. Findings revealed distinct linguistic features associated with BPD, based on Reddit posts, which differentiated these users from a control group. Language patterns were also found to be associated with the occurrence of maladaptive thoughts and behaviours. Thus, this study demonstrates that there are indeed linguistic markers of BPD present on social media. It also implies that language could be predictive of maladaptive thoughts and behaviours associated with BPD. These findings are of importance as they suggest potential for clinical interventions to be provided based on the language of people with BPD to try to reduce the likelihood of maladaptive thoughts and behaviours occurring. For example, by social media tracking or engaging people with BPD in expressive writing therapy. Overall, this study has provided a greater understanding of the disorder and how it manifests through language and behaviour.

Keywords: behaviour analysis, borderline personality disorder, natural language processing, social media data

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Authors: Saddam Hussain, Ghadeer Mohsen Albadrani

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Pakistan is one of the most vulnerable countries to climate change. Being a country where 23% of the country’s GDP relies on agriculture, this is a serious cause of concern. Introducing industrial hemp in Pakistan can help build climate resilience in the agricultural sector of the country, as hemp has recently emerged as a sustainable, eco-friendly, resource-efficient, and climate-resilient crop globally. Hemp has the potential to absorb huge amounts of CO₂, nourish the soil, and be used to create various biodegradable and eco-friendly products. Hemp is twice as effective as trees at absorbing and locking up carbon, with 1 hectare (2.5 acres) of hemp reckoned to absorb 8 to 22 tonnes of CO₂ a year, more than any woodland. Along with its high carbon-sequestration ability, it produces higher biomass and can be successfully grown as a cover crop. Hemp can grow in almost all soil conditions and does not require pesticides. It has fast-growing qualities and needs only 120 days to be ready for harvest. Compared with cotton, hemp requires 50% less water to grow and can produce three times higher fiber yield with a lower ecological footprint. Recently, the Government of Pakistan has allowed the cultivation of industrial hemp for industrial and medicinal purposes, making it possible for hemp to be reinserted into the country’s economy. Pakistan’s agro-climatic and edaphic conditions are well-suitable to produce industrial hemp, and its cultivation can bring economic benefits to the country. Pakistan can enter global markets as a new exporter of hemp products. The production of hemp in Pakistan can be most exciting to the workforce, especially for farmers participating in hemp markets. The minimum production cost of hemp makes it affordable to small holding farmers, especially those who need their cropping system to be as highly sustainable as possible. Dr. Saddam Hussain is leading the first pilot project of Industrial Hemp in Pakistan. In the past three years, he has been able to recruit high-impact research grants on industrial hemp as Principal Investigator. He has already screened the non-toxic hemp genotypes, tested the adaptability of exotic material in various agroecological conditions, formulated the production agronomy, and successfully developed the complete value chain. He has developed prototypes (fabric, denim, knitwear) using hemp fibre in collaboration with industrial partners and has optimized the indigenous fibre processing techniques. In this lecture, Dr. Hussain will talk on hemp agronomy and its complete fibre value chain. He will discuss the current progress, and will highlight the major challenges and future research direction on hemp research.

Keywords: industrial hemp, agricultural sustainability, agronomic evaluation, hemp value chain

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Authors: Mokhlisur Rahman

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The growing consensus among scientists and world leaders indicates that immediate action should be considered regarding the climate change phenomenon. However, climate change is no more a global issue but a personal one. Thus, individual participation is necessary to address such a significant issue. Studies show that individuals who perceive climate change as a personal issue are more likely to act toward it. This abstract presents augmented reality (A.R.) technology in the social media platform Facebook video advertising. The idea involves creating a video advertisement that enables users to interact with the video by navigating its features and experiencing the result uniquely and engagingly. This advertisement uses A.R. to bring changes, such as people making changes in real-life scenarios by simple clicks on the video and hearing an instant rewarding fact about their choices. The video shows three options: room, lawn, and driveway. Users select one option and engage in interaction based on while holding the camera in their personal spaces: Suppose users select the first option, room, and hold their camera toward spots such as by the windows, balcony, corners, and even walls. In that case, the A.R. offers users different plants appropriate for those unoccupied spaces in the room. Users can change the options of the plants and see which space at their house deserves a plant that makes it more natural. When a user adds a natural element to the video, the video content explains a piece of beneficiary information about how the user contributes to the world more to be livable and why it is necessary. With the help of A.R., if users select the second option, lawn, and hold their camera toward their lawn, the options are various small trees for their lawn to make it more environmentally friendly and decorative. The video plays a beneficiary explanation here too. Suppose users select the third option, driveway, and hold their camera toward their driveway. In that case, the A.R. video option offers unique recycle bin designs using A.I. measurement of spaces. The video plays audio information on anthropogenic contribution to greenhouse gas emission. IoT embeds tracking code in the video ad on Facebook, which stores the exact number of views in the cloud for data analysis. An online survey at the end collects short qualitative answers. This study helps understand the number of users involved and willing to change their behavior; It makes personalized advertising in social media. Considering the current state of climate change, the urgency for action is increasing. This ad increases the chance to make direct connections with individuals and gives a sense of personal responsibility for climate change to act

Keywords: motivations, climate, iot, personalized-advertising, action

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Authors: Maged El-Sayed Mohamed

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Eucalyptus camaldulensis is one on the most well-known species of the genus Eucalyptus in the Middle east, its importance relay on the high production of its unique volatile constituents which exhibits many medicinal and pharmacological activities. The gall-forming wasp (Leptocybe invasa) has recently come into sight as the main pest attacking E. camaldulensis and causing severe injury. The wasp lays its eggs in the petiole and midrib of leaves and stems of young shoots of E. camaldulensis, which leads to gall formation. Gall formation by L. invasa damages growing shoot and leaves of Eucalyptus, resulting in abscission of leaves and drying. AIM: This study is an attempt to investigate the effect of the gall wasp (Leptocybe invasa) attack on the volatile constitutes of E. camaldulensis. This could help in the control of this wasp through stimulating plant defenses or production of a new allelochemicals or insecticide. The study of volatile constitutes of Eucalyptus before and after attack by the wasp can help the re-use and recycle of the infected Eucalyptus trees for new pharmacological and medicinal activities. Methodology: The fresh gall wasp-attacked and healthy leaves (100 g each) were cut and immediately subjected to hydrodistillation using Clevenger-type apparatus for 3 hours. The volatile fractions isolated were analyzed using Gas chromatography/mass spectrometry (GC/MS). Kovat’s retention indices (RI) were calculated with respect to a set of co-injected standard hydrocarbons (C10-C28). Compounds were identified by comparing their spectral data and retention indices with Wiley Registry of Mass Spectral Data 10th edition (April 2013), NIST 11 Mass Spectral Library (NIST11/2011/EPA/NIH) and literature data. Results: Fifty-nine components representing 89.13 and 88.60% of the total volatile fraction content respectively were quantitatively analyzed. Twenty-six major compounds at an average concentration greater than 0.1 ± 0.02% have been used for the statistical comparison. From those major components, twenty-one were found in both the attacked and healthy Eucalyptus leaves’ fractions in different concentration and five components, mono terpene p-Mentha-2-4(8) diene and the sesquiterpenes δ-elemene, β-elemene, E-caryophyllene and Bicyclogermacrene, were unique and only produced in the attacked-leaves’ fraction. CONCLUSION: Newly produced components or those commonly found in the volatile fraction and changed in concentration could represent a part of the plant defense mechanisms or might be an element of the plant allelopathic and communication mechanisms. Identification of the components of the gall wasp-damaged leaves can help in their recycling for different physiological, pharmacological and medicinal uses.

Keywords: Eucalyptus camaldulensis, eucalyptus recycling, gall wasp, Leptocybe invasa, plant defense mechanisms, Terpene fraction

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Authors: S. I. Mwasha, Z. Robinson, M. Musgrave

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Communities, especially in the global south, have been reported to have low adaptive capacity to cope with climate change impacts. As an attempt to improve adaptive capacity, most studies have focused on understanding the access of the household resources which can contribute to resilience against changes. However, little attention has been shown in uncovering how the household resources could be used and their implications to resilience against weather related shocks. By using a case study qualitative study, this project analyzed the trends in livelihoods practices and their implication to social equity. The study was done in three different villages within Kilimanjaro region. Each in different agro ecological zone. Two focus group discussions in two agro-ecological zones were done, one for women and another one for men except in the third zone where focus group participant were combined together (due to unforeseen circumstances). In the focus group discussion, several participatory rural appraisal tools were used to understand trend in crops and animal production and the use in which it is made: climate trends, soil fertility, trees and other livelihoods resources. Data were analyzed using thematic network analysis. Using an amalgam of magnitude (to note weather comments made were positive or negative) and descriptive coding (to note the topic), six basic themes were identified under social equity: individual ownership, family ownership, love and respect, women no education, women access to education as well as women access to loans. The results implied that despite mum and dad in the family providing labor in the agro pastoral activities, there were separations on who own what, as well as individual obligations in the family. Dad owned mostly income creating crops and mum, food crops. therefore, men controlled the economy which made some of them become arrogant and spend money to meet their interests sometimes not taking care of the family. Separation in ownership was reported to contribute to conflicts in the household as well as causing controversy on the use income is spent. Men were reported to use income to promote matriarchy system. However, as women were capacitated through access to education and loans they become closer to their husband and get access to own and plan the income together for the interest of the family. Joint ownership and planning on the household resources were reported to be important if families have to better adapt to climate change. The aim of this study is not to show women empowerment and joint ownership and planning as only remedy for low adaptive capacity. There is the need to understand other practices that either directly or indirectly impacts environmental integrity, food security and economic development for household resilience against changing climate.

Keywords: adaptive capacity, climate change, resilience, women empowerment

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Authors: Alexis D'Agostino, Amanda Pomeroy

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Background: Resource availability is essential to effective implementation of national nutrition policies. To this end, the SPRING Project has collected and analyzed budget data from government ministries in Uganda, international donors, and other nutrition implementers to provide data for the first time on what funding is actually allocated to implement nutrition activities named in the national nutrition plan. Methodology: USAID’s SPRING Project used the Uganda Nutrition Action Plan (UNAP) as the starting point for budget analysis. Thorough desk reviews of public budgets from government, donors, and NGOs were mapped to activities named in the UNAP and validated by key informants (KIs) across the stakeholder groups. By relying on nationally-recognized and locally-created documents, SPRING provided a familiar basis for discussions to increase credibility and local ownership of findings. Among other things, the KIs validated the amount, source, and type (specific or sensitive) of funding. When only high-level budget data were available, KIs provided rough estimates of the percentage of allocations that were actually nutrition-relevant, allowing creation of confidence intervals around some funding estimates. Results: After validating data and narrowing in on estimates of funding to nutrition-relevant programming, researchers applied a formula to estimate overall nutrition allocations. In line with guidance by the SUN Movement and its three-step process, nutrition-specific funding was counted at 100% of its allocation amount, while nutrition sensitive funding was counted at 25%. The vast majority of nutrition funding in Uganda is off-budget, with over 90 percent of all nutrition funding is provided outside of the government system. Overall allocations are split nearly evenly between nutrition-specific and –sensitive activities. In FY 2013/14, the two-year study’s baseline year, on- and off-budget funding for nutrition was estimated to be around 60 million USD. While the 60 million USD allocations compare favorably to the 66 million USD estimate of the cost of the UNAP, not all activities are sufficiently funded. Those activities with a focus on behavior change were the most underfunded. In addition, accompanying qualitative research suggested that donor funding for nutrition activities may shift government funding into other areas of work, making it difficult to estimate the sustainability of current nutrition investments.Conclusions: Beyond providing figures, these estimates can be used together with the qualitative results of the study to explain how and why these amounts were allocated for particular activities and not others, examine the negotiation process that occurred, and suggest options for improving the flow of finances to UNAP activities for the remainder of the policy tenure. By the end of the PBN study, several years of nutrition budget estimates will be available to compare changes in funding over time. Halfway through SPRING’s work, there is evidence that country stakeholders have begun to feel ownership over the ultimate findings and some ministries are requesting increased technical assistance in nutrition budgeting. Ultimately, these data can be used within organization to advocate for more and improved nutrition funding and to improve targeting of nutrition allocations.

Keywords: budget, nutrition, financing, scale-up

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Authors: Otuwose E. Agyeno, Adeniyi A. Jayeola, Bashir A. Ajala

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P. esculentus is indigenous to Nigeria yet no wild relation has been encountered or reported. This has made it difficult to establish proper lineages between the varieties and landraces under cultivation. The present work is the first to determine the apormophy of 135 morphoanatomical characters in organs of 46 accessions drawn from 23 populations of this species based on dicta. The character states were coded in accession x character-state matrices and only 83 were informative and utilised for neighbour joining clustering based on euclidean values, and heuristic search in parsimony analysis using PAST ver. 3.15 software. Compatibility and evolutionary trends between accessions were then explored from values and diagrams produced. The low consistency indices (CI) recorded support monophyly and low homoplasy in this taxon. Agglomerative schedules based on character type and source data sets divided the accessions into mainly 3 clades, each of complexes of accessions. Solenostemon rotundifolius (Poir) J.K Morton was the outgroup (OG) used, and it occurred within the largest clades except when the characters were combined in a data set. The OG showed better compatibility with accessions of populations of landrace Isci, and varieties Riyum and Long’at. Otherwise, its aerial parts are more consistent with those of accessions of variety Bebot. The highly polytomous clades produced due to anatomical data set may be an indication of how stable such characters are in this species. Strict consensus trees with more than 60 nodes outputted showed that the basal nodes were strongly supported by 3 to 17 characters across the data sets, suggesting that populations of this species are more alike. The OG was clearly the first diverging lineage and closely related to accessions of landrace Gwe and variety Bebot morphologically, but different from them anatomically. It was also distantly related to landrace Fina and variety Long’at in terms of root, stem and leaf structural attributes. There were at least 5 other clades with each comprising of complexes of accessions from different localities and terrains within the study area. Spherical stem in cross section, size of vascular bundles at the stem corners as well as the alternate and whorl phyllotaxy are attributes which may have facilitated each other’s evolution in all accessions of the landrace Gwe, and they may be innovative since such states are not characteristic of the larger Lamiaceae, and Plectranthus L’Her in particular. In conclusion, this study has provided valuable information about infraspecific diversity in this taxon. It supports recognition of the varietal statuses accorded to populations of P. esculentus, as well as the hypothesis that the wild gene might have been distributed on the Jos Plateau. However, molecular characterisation of accessions of populations of this species would resolve this problem better.

Keywords: clustering, lineage, morphoanatomical characters, Nigeria, phylogenetics, Plectranthus esculentus, population

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Authors: A. M. Tarola, R. Preti, A. M. Girelli, P. Campana

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Goat dairy products are gaining popularity worldwide. In developing countries, but also in many marginal regions of the Mediterranean area, goats represent a great part of the economy and ensure food security. In fact, these small ruminants are able to convert efficiently poor weedy plants and small trees into traditional products of high nutritional quality, showing great resilience to different climatic and environmental conditions. In developed countries, goat milk is appreciated for the presence of health-promoting compounds, bioactive compounds such as conjugated linoleic acids, oligosaccharides, sphingolipids and polyammines. This paper focuses on the recent advances in literature on the nutritional properties of goat milk and on innovative techniques to improve its quality as to become a promising functional food. The environmental sustainability of different methodologies of production has also been examined. Goat milk is valued today as a food of high nutritional value and functional properties as well as small environmental footprint. It is widely consumed in many countries due to high nutritional value, lower allergenic potential, and better digestibility when compared to bovine milk, that makes this product suitable for infants, elderly or sensitive patients. The main differences in chemical composition between a cow and goat milk rely on fat globules that in goat milk are smaller and in fatty acids that present a smaller chain length, while protein, fat, and lactose concentration are comparable. Milk nutritional properties have demonstrated to be strongly influenced by animal diet, genotype, and welfare, but also by season and production systems. Furthermore, there is a growing interest in the dairy industry in goat milk for its relatively high concentration of prebiotics and a good amount of probiotics, which have recently gained importance for their therapeutic potential. Therefore, goat milk is studied as a promising matrix to develop innovative functional foods. In addition to the economic and nutritional value, goat milk is considered a sustainable product for its small environmental footprint, as they require relatively little water and land, and less medical treatments, compared to cow, these characteristics make its production naturally vocated to organic farming. Organic goat milk production has becoming more and more interesting both for farmers and consumers as it can answer to several concerns like environment protection, animal welfare and economical sustainment of rural populations living in marginal lands. These evidences make goat milk an ancient food with novel properties and advantages to be valorized and exploited.

Keywords: goat milk, nutritional quality, bioactive compounds, sustainable production, animal welfare

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Authors: Matias Hargreaves, Martin Del Valle, Diego Rodriguez, Riveros Jose Luis

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Trough years, all kind of social development projects have tried to solve social problems such as hunger, poverty, malnutrition, food insecurity, among others, with poor success. Both private and state initiatives have invested resources in several countries and communities. Nevertheless, most of these initiatives are scientific or external developers-centered, with a lack of local participation. This compromises the sustainability of any intervention and also leads to a poor empowerment of local community. The participatory approach aims to rescue and enhance the local knowledge since it recognizes that this kind of problems are better known by native actors. The objective of the study was to describe the role played by the community empowerment on food security improvement in the NGO “O Viveiro” (15°43'37.77"S; 32°46'27.53"E) and Barrio Broma village (15°43'58.78"S; 32°46'7.27"E) in Chitima, Mozambique. A center for training in goat livestock and orchard was build. A community orchard was co-constructed between foreign technicians and local actors. The prototype was installed in February, 2016 by the technician team and local community with 16 m2 as a nursery garden. Two orchard workshops were conducted in order to design a sustainable productive model which mixes both local and technological approaches. Two goat meat workshops were conducted in order to describe local methods and train the community to conduce their own techniques with high sanitary and productive standards. Technician team stayed in Mozambique until May, 2016. The quorum for the orchard workshops was 20 and 14 persons respectively, which represents 100% and 70%of the total requested quorum (20). For the goat meat workshops were 4 and 5 persons, which representa80% and 100% of the total requested quorum (5). Until August, 2016, the orchard is 3.219 m2 and it grows several vegetables as beans, chili pepper, garlic, onion, tomatoes, lettuce, sweet potato, yuca potato, cabbage, eggplant, papaya trees, mango, and cassava. The process of increasing in size and diversification of vegetables grown was led entirely by the local community. In connection with this, the local community started to harvest and began to sell the vegetable products at the local market. At the meat goat workshops, local participants rescued a local knowledge by describing and practicing a traditional way to process goat meat by drying it outdoors and then doing a smoked treatment. This information might contribute to describe the level of empowerment of this community, and thus give evidence of acceptance of foreign intervention for improving their own proceedings and traditions.

Keywords: children malnutrition, food security, Local community, participatory approach

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Authors: Zanele Ntshidi, Sebinasi Dzikiti, Dominic Mazvimavi

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South Africa is a dry country and yet it is ranked as the 8th largest exporter of fresh apples (Malus Domestica) globally. Prime apple producing regions are in the Eastern and Western Cape Provinces of the country where all the fruit is grown under irrigation. Climate change models predict increasingly drier future conditions in these regions and the frequency and severity of droughts is expected to increase. For the sustainability and growth of the fruit industry it is important to minimize non-beneficial water losses from the orchard floor. The aims of this study were firstly to compare the water use of cover crop species used in South African orchards for which there is currently no information. The second aim was to investigate how orchard water use (evapotranspiration) was partitioned into beneficial (tree transpiration) and non-beneficial (orchard floor evaporation) water uses for micro-sprinkler irrigated orchards with different canopy covers. This information is important in order to explore opportunities to minimize non-beneficial water losses. Six cover crop species (four exotic and two indigenous) were grown in 2 L pots in a greenhouse. Cover crop transpiration was measured using the gravimetric method on clear days. To establish how water use was partitioned in orchards, evapotranspiration (ET) was measured using an open path eddy covariance system, while tree transpiration was measured hourly throughout the season (October to June) on six trees per orchard using the heat ratio sap flow method. On selected clear days, soil evaporation was measured hourly from sunrise to sunset using six micro-lysimeters situated at different wet/dry and sun/shade positions on the orchard floor. Transpiration of cover crops was measured using miniature (2 mm Ø) stem heat balance sap flow gauges. The greenhouse study showed that exotic cover crops had significantly higher (p < 0.01) average transpiration rates (~3.7 L/m2/d) than the indigenous species (~ 2.2 L/m²/d). In young non-bearing orchards, orchard floor evaporative fluxes accounted for more than 60% of orchard ET while this ranged from 10 to 30% in mature orchards with a high canopy cover. While exotic cover crops are preferred by most farmers, this study shows that they use larger quantities of water than indigenous species. This in turn contributes to a larger orchard floor evaporation flux. In young orchards non-beneficial losses can be minimized by adopting drip or short range micro-sprinkler methods that reduce the wetted soil fraction thereby conserving water.

Keywords: evapotranspiration, sap flow, soil evaporation, transpiration

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Authors: Bander Alzahrani, Mohammed Alreshoodi

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Information-centric networking (ICN) using architectures such as the Publish-Subscribe Internet Technology (PURSUIT) has been proposed as a new networking model that aims at replacing the current used end-centric networking model of the Internet. This emerged model focuses on what is being exchanged rather than which network entities are exchanging information, which gives the control plane functions such as routing and host location the ability to be specified according to the content items. The forwarding plane of the PURSUIT ICN architecture uses a simple and light mechanism based on Bloom filter technologies to forward the packets. Although this forwarding scheme solve many problems of the today’s Internet such as the growth of the routing table and the scalability issues, it is vulnerable to brute force attacks which are starting point to distributed- denial-of-service (DDoS) attacks. In this work, we design and analyze a novel source-routing and information delivery technique that keeps the simplicity of using Bloom filter-based forwarding while being able to deter different attacks such as denial of service attacks at the ingress of the network. To achieve this, special forwarding nodes called Edge-FW are directly attached to end user nodes and used to perform a security test for malicious injected random packets at the ingress of the path to prevent any possible attack brute force attacks at early stage. In this technique, a core entity of the PURSUIT ICN architecture called topology manager, that is responsible for finding shortest path and creating a forwarding identifiers (FId), uses a cryptographically secure hash function to create a 64-bit hash, h, over the formed FId for authentication purpose to be included in the packet. Our proposal restricts the attacker from injecting packets carrying random FIds with a high amount of filling factor ρ, by optimizing and reducing the maximum allowed filling factor ρm in the network. We optimize the FId to the minimum possible filling factor where ρ ≤ ρm, while it supports longer delivery trees, so the network scalability is not affected by the chosen ρm. With this scheme, the filling factor of any legitimate FId never exceeds the ρm while the filling factor of illegitimate FIds cannot exceed the chosen small value of ρm. Therefore, injecting a packet containing an FId with a large value of filling factor, to achieve higher attack probability, is not possible anymore. The preliminary analysis of this proposal indicates that with the designed scheme, the forwarding function can detect and prevent malicious activities such DDoS attacks at early stage and with very high probability.

Keywords: forwarding identifier, filling factor, information centric network, topology manager

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Authors: Mariam Anwaar, Kiran B. Ahmad

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Borderline Personality Disorder (BPD) is an invasive presence of affect instability, disturbance in self-concept and attachment in relationships. The profound indicator is the dichotomous approach of the world in which the ego categorizes individuals, especially their significant others, into secure or threatful beings, leaving little room for a complex combination of characteristics in one person. This defense mechanism of splitting their world has been described through the explanatory model of unconscious conflict theorized by Sigmund Freud’s Electra Complex in the Phallic Stage. The central role is of the father with whom the daughter experiences penis envy, thus identifying with the mother’s characteristics to receive the father’s attention. However, Margret Mahler, an object relation theorist, elucidates the central role of the mother and that the split occurs during the pre-Electra complex stage. Amid the 14 and 24 months of the infant, it acknowledges the world away from the mother as they have developed milestones such as crawling. In such novelty, the infant crawls away from the mother creating a sense of independence (individuation). On the other hand, being distant causes anxiety, making them return to their original object of security (separation). In BPD, the separation-individuation stage is disrupted, due to contradictory actions of the caregiver, which results in splitting the object into negative and positive aspects, repressing the former and adhering to the latter for survival. Thus, with time, the ego distorts the reality into dichotomous categories, using the splitting defenses, and the mental representation of the self is distorted due to the internalization of the negative objects. The explanatory model was recognized in the case study of Fizza, at 21-year-old Pakistani female, residing in Karachi. Her marital status is single with an occupation being a dental student. Fizza lives in a nuclear family but is surrounded by her extended family as they all are in close vicinity. She came with the complaints of depressive symptoms for two-years along with self-harm due to severe family conflicts. Through the intervention of Dialectical Behavior Therapy (DBT), the self-harming actions were reduced, however, this libidinal energy transformed into claustrophobic symptoms and, along with this, Fizza has always experienced vivid dreams. A retrospective method of Jungian dream-analysis was applied to locate the origins of the splitting in the unconscious. The result was the revelation of a sexual harassment trauma at the age of six-years which was displaced in the form of self-harm. In addition to this, the presence of a conflict at the separation-individuation stage was detected during the dream-analysis, and it was the underlying explanation of the claustrophobic symptoms. This qualitative case study implicates the use of a patient’s subjective experiences, such as dreams, to journey through the spiral of the unconscious in order to not only detect repressed memories but to use them in psychotherapy as a means of healing the patient.

Keywords: borderline personality disorder, dream-analysis, Electra complex, separation-individuation, splitting, unconscious

Procedia PDF Downloads 153

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: Nasser Koleini Mamaghani, Sara Mostowfi

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The complexity of public space design makes it difficult for designers to simultaneously consider all issues for thorough decision-making. Among public spaces, the public space around people’s house is the most prominent space that affects and impacts people’s daily life. Considering recreational public spaces in cities, their main purpose would be to design for experiences that enable a deep feeling of peace and a moment of being away from the hectic daily life. Respecting human emotions and restoring natural environments, although difficult and to some extent out of reach, are key issues for designing such spaces. In this paper we propose to analyse the structure of recreational public spaces and the related emotional impressions. Furthermore, we suggest investigating how these structures influence people’s choice for public spaces by using differential semantics. According to Kansei methodology, in order to evaluate a situation appropriately, the assessment variables must be adapted to the user’s mental scheme. This means that the first step would have to be the identification of a space’s conceptual scheme. In our case study, 32 Kansei words and 4 different locations, each with a different sensual experience, were selected. The 4 locations were all parks in the city of Tehran (Iran), each with a unique structure and artifacts such as a fountain, lighting, sculptures, and music. It should be noted that each of these parks has different combination and structure of environmental and artificial elements like: fountain, lightning, sculpture, music (sound) and so forth. The first one was park No.1, a park with natural environment, the selected space was a fountain with motion light and sculpture. The second park was park No.2, in which there are different styles of park construction: ways from different countries, the selected space was traditional Iranian architecture with a fountain and trees. The third one was park No.3, the park with modern environment and spaces, and included a fountain that moved according to music and lighting. The fourth park was park No.4, the park with combination of four elements: water, fire, earth, wind, the selected space was fountains squirting water from the ground up. 80 participant (55 males and 25 females) aged from 20-60 years participated in this experiment. Each person filled the questionnaire in the park he/she was in. Five-point semantic differential scale was considered to determine the relation between space details and adjectives (kansei words). Received data were analyzed by multivariate statistical technique (factor analysis using SPSS statics). Finally the results of this analysis are criteria as inspiration which can be used in future space designing for creating pleasant feeling in users.

Keywords: environmental design, differential semantics, Kansei engineering, subjective preferences, space

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Authors: Gerd Wilsch, Tobias Guenther, Tobias Voelker

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In view of the ageing of vital infrastructure facilities, a reliable condition assessment of concrete structures is becoming of increasing interest for asset owners to plan timely and appropriate maintenance and repair interventions. For concrete structures, reinforcement corrosion induced by penetrating chlorides is the dominant deterioration mechanism affecting the serviceability and, eventually, structural performance. The determination of the quantitative chloride ingress is required not only to provide valuable information on the present condition of a structure, but the data obtained can also be used for the prediction of its future development and associated risks. At present, wet chemical analysis of ground concrete samples by a laboratory is the most common test procedure for the determination of the chloride content. As the chloride content is expressed by the mass of the binder, the analysis should involve determination of both the amount of binder and the amount of chloride contained in a concrete sample. This procedure is laborious, time-consuming, and costly. The chloride profile obtained is based on depth intervals of 10 mm. LIBS is an economically viable alternative providing chloride contents at depth intervals of 1 mm or less. It provides two-dimensional maps of quantitative element distributions and can locate spots of higher concentrations like in a crack. The results are correlated directly to the mass of the binder, and it can be applied on-site to deliver instantaneous results for the evaluation of the structure. Examples for the application of the method in the laboratory for the investigation of diffusion and migration of chlorides, sulfates, and alkalis are presented. An example for the visualization of the Li transport in concrete is also shown. These examples show the potential of the method for a fast, reliable, and automated two-dimensional investigation of transport processes. Due to the better spatial resolution, more accurate input parameters for model calculations are determined. By the simultaneous detection of elements such as carbon, chlorine, sodium, and potassium, the mutual influence of the different processes can be determined in only one measurement. Furthermore, the application of a mobile LIBS system in a parking garage is demonstrated. It uses a diode-pumped low energy laser (3 mJ, 1.5 ns, 100 Hz) and a compact NIR spectrometer. A portable scanner allows a two-dimensional quantitative element mapping. Results show the quantitative chloride analysis on wall and floor surfaces. To determine the 2-D distribution of harmful elements (Cl, C), concrete cores were drilled, split, and analyzed directly on-site. Results obtained were compared and verified with laboratory measurements. The results presented show that the LIBS method is a valuable addition to the standard procedures - the wet chemical analysis of ground concrete samples. Currently, work is underway to develop a technical code of practice for the application of the method for the determination of chloride concentration in concrete.

Keywords: chemical analysis, concrete, LIBS, spectroscopy

Procedia PDF Downloads 105

Authors: Omar Romero-Hernandez, Federico Castillo, Armando Sanchez, Sergio Romero, Andrea Romero, Michael Mitchell

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Environmental policies for resource conservation in rural areas include subsidies on services and social programs to cover living expenses. Government's expectation is that rural communities who benefit from social programs, such as payment for ecosystem services, are provided with an incentive to conserve natural resources and preserve natural sinks for greenhouse gases. At the same time, global climate change has affected the lives of people worldwide. The capability to adapt to global warming depends on the available resources and the standard of living, putting rural communities at a disadvantage. This paper explores whether rural entrepreneurship can represent a solution to resource conservation and global warming adaptation in rural communities. The research focuses on a sample of two coffee communities in Oaxaca, Mexico. Researchers used geospatial information contained in aerial photographs of the geographical areas of interest. Households were identified in the photos via the roofs of households and georeferenced via coordinates. From the household population, a random selection of roofs was performed and received a visit. A total of 112 surveys were completed, including questions of socio-demographics, perception to climate change and adaptation activities. The population includes two groups of study: entrepreneurs and non-entrepreneurs. Data was sorted, filtered, and validated. Analysis includes descriptive statistics for exploratory purposes and a multi-regression analysis. Outcomes from the surveys indicate that coffee farmers, who demonstrate entrepreneurship skills and hire employees, are more eager to adapt to climate change despite the extreme adverse socioeconomic conditions of the region. We show that farmers with entrepreneurial tendencies are more creative in using innovative farm practices such as the planting of shade trees, the use of live fencing, instead of wires, and watershed protection techniques, among others. This result counters the notion that small farmers are at the mercy of climate change and have no possibility of being able to adapt to a changing climate. The study also points to roadblocks that farmers face when coping with climate change. Among those roadblocks are a lack of extension services, access to credit, and reliable internet, all of which reduces access to vital information needed in today’s constantly changing world. Results indicate that, under some circumstances, funding and supporting entrepreneurship programs may provide more benefit than traditional social programs.

Keywords: entrepreneurship, global warming, rural communities, climate change adaptation

Procedia PDF Downloads 239

Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

Procedia PDF Downloads 106

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Rafael Alexandre Dos Reis

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Research has shown a substantial increase in the participation of Conventionally Fuelled Vehicles (CFVs) in the urban transport modal split. The reasons for this unsustainable reality are multiple, from economic interventions to individual behaviour. The development and delivery of positive incentives for the adoption of more environmental-friendly modes of transport is an emerging strategy to help in tackling the problem of excessive use of conventionally fuelled vehicles. The efficiency of this approach, like other information-based schemes, can benefit from the knowledge of their potential impacts in theoretical constructs of multiple behaviour change theories. The goal of this research is to critically analyse theories of behaviour that are relevant to transport research and the impacts of positive incentives on the theoretical determinants of behaviour, strengthening the current body of evidence about the benefits of this approach. The main method to investigate this will involve a literature review on two main topics: the current theories of behaviour that have empirical support in transport research and the past or ongoing positive incentives programs that had an impact on car use reduction. The reviewed programs of positive incentives were the following: The TravelSmart®; Spitsmijden®; Incentives for Singapore Commuters® (INSINC); COMMUTEGREENER®; MOVESMARTER®; STREETLIFE®; SUPERHUB®; SUNSET® and the EMPOWER® project. The theories analysed were the heory of Planned Behaviour (TPB); The Norm Activation Theory (NAM); Social Learning Theory (SLT); The Theory of Interpersonal Behaviour (TIB); The Goal-Setting Theory (GST) and The Value-Belief-Norm Theory (VBN). After the revisions of the theoretical constructs of each of the theories and their influence on car use, it can be concluded that positive incentives schemes impact on behaviour change in the following manners: -Changing individual’s attitudes through informational incentives; -Increasing feelings of moral obligations to reduce the use of CFVs; -Increase the perceived social pressure to engage in more sustainable mobility behaviours through the use of comparison mechanisms in social media, for example; -Increase the perceived control of behaviour through informational incentives and training incentives; -Increasing personal norms with reinforcing information; -Providing tools for self-monitoring and self-evaluation; -Providing real experiences in alternative modes to the car; -Making the observation of others’ car use reduction possible; -Informing about consequences of behaviour and emphasizing the individual’s responsibility with society and the environment; -Increasing the perception of the consequences of car use to an individual’s valued objects; -Increasing the perceived ability to reduce threats to environment; -Help establishing goals to reduce car use; - iving personalized feedback on the goal; -Increase feelings of commitment to the goal; -Reducing the perceived complexity of the use of alternatives to the car. It is notable that the emerging technique of delivering positive incentives are systematically connected to causal determinants of travel behaviour. The preliminary results of the reviewed programs evidence how positive incentives might strengthen these determinants and help in the process of behaviour change.

Keywords: positive incentives, private car use reduction, sustainable behaviour, voluntary travel behaviour change

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Authors: Rena Upitis, Philip C. Abrami, Karen Boese

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The success of one-on-one music study relies heavily on the ability of the teacher to provide sufficient direction to students during weekly lessons so that they can successfully practice from one lesson to the next. Traditionally, these instructions are given in a paper notebook, where the teacher makes notes for the students after describing a task or demonstrating a technique. The ability of students to make sense of these notes varies according to their understanding of the teacher’s directions, their motivation to practice, their memory of the lesson, and their abilities to self-regulate. At best, the notes enable the student to progress successfully. At worst, the student is left rudderless until the next lesson takes place. Digital notebooks have the potential to provide a more interactive and effective bridge between music lessons than traditional pen-and-paper notebooks. One such digital notebook, Cadenza, was designed to streamline and improve teachers’ instruction, to enhance student practicing, and to provide the means for teachers and students to communicate between lessons. For example, Cadenza contains a video annotator, where teachers can offer real-time guidance on uploaded student performances. Using the checklist feature, teachers and students negotiate the frequency and type of practice during the lesson, which the student can then access during subsequent practice sessions. Following the tenets of self-regulated learning, goal setting and reflection are also featured. Accordingly, the present paper addressed the following research questions: (1) How does the use of the Cadenza digital music notebook engage students and their teachers?, (2) Which features of Cadenza are most successful?, (3) Which features could be improved?, and (4) Is student learning and motivation enhanced with the use of the Cadenza digital music notebook? The paper describes the results 10 months of field-testing of Cadenza, structured around the four research questions outlined. Six teachers and 65 students took part in the study. Data were collected through video-recorded lesson observations, digital screen captures, surveys, and interviews. Standard qualitative protocols for coding results and identifying themes were employed to analyze the results. The results consistently indicated that teachers and students embraced the digital platform offered by Cadenza. The practice log and timer, the real-time annotation tool, the checklists, the lesson summaries, and the commenting features were found to be the most valuable functions, by students and teachers alike. Teachers also reported that students progressed more quickly with Cadenza, and received higher results in examinations than those students who were not using Cadenza. Teachers identified modifications to Cadenza that would make it an even more powerful way to support student learning. These modifications, once implemented, will move the tool well past its traditional notebook uses to new ways of motivating students to practise between lessons and to communicate with teachers about their learning. Improvements to the tool called for by the teachers included the ability to duplicate archived lessons, allowing for split screen viewing, and adding goal setting to the teacher window. In the concluding section, proposed modifications and their implications for self-regulated learning are discussed.

Keywords: digital music technologies, electronic notebooks, self-regulated learning, studio music instruction

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Authors: Maike Andresen, Georg Dochtmann

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Due to political, social, and societal changes in labor organization, top-sharing, defined as job-sharing in leading positions, becomes more important in HRM. German companies are looking for practical and economically meaningful solutions that allow to enduringly increase women’s ratio in management, not only because of a recently implemented quota. Furthermore, supporting employees in achieving work-life balance is perceived as an important goal for a sustainable HRM to gain competitive advantage. Top-sharing is seen as being suitable to reach both goals. To evaluate determinants leading to effective top-sharing, a case study of a newly implemented top-sharing tandem in a large German enterprise was conducted over a period of 15 months. In this company, a full leadership position was split into two 60%-part-time positions held by an experienced female leader in her late career and a female college who took over her first leadership position (mid-career). We assumed a person-person fit in terms of a match of the top sharing partners’ personality profiles (Big Five) and their leadership motivations to be important prerequisites for an effective collaboration between them. We evaluated the person-person fit variables once before the tandem started to work. Both leaders were expected to learn from each other (mentoring, competency development). On an operational level, they were supposed to lead together the same employees in an effective manner (leader-member exchange), presupposing an effective cooperation between both (handing over information). To see developments over time, these processes were evaluated three times over the span of the project. Top-Sharing and the underlined processes are expected to positively influence the tandem’s performance which has been evaluated twice, at the beginning and the end of the project, to assess its development over time as well. The evaluation of the personality and the basic motives suggests that both executives can be a successful top-sharing tandem. The competency evaluations (supervisor as well as self-assessment) increased over the time span. Although the top sharing tandem worked on equal terms, they implemented rather classical than peer-mentoring due to different career ambitions of the tandem partners. Thus, opportunities were not used completely. Team-member exchange scores proved the good cooperation between the top-sharers. Although the employees did not evaluate the leader-member-exchange between them and the two leaders of the tandem homogeneously, the top-sharing tandem itself did not have the impression that the employees’ task performance depended on whom of the tandem was responsible for the task. Furthermore, top-sharing did not negatively influence the performance of both leaders. During qualitative interviews with the top-sharers and their team, we found that the top-sharers could focus more easily on their tasks. The results suggest positive outcomes of top-sharing (e.g. competency improvement, learning from each other through mentoring). Top-Sharing does not hamper performance. Thus, further research and practical implementations are suggested. As part-time jobs are still more often a female solution to increase their work-life- and work-family-balance, top-sharing may be a suitable solution to increase the woman’s ratio in leadership positions as well as to sustainable increase work-life-balance of executives.

Keywords: mentoring, part-time leadership, top-sharing, work-life-balance

Procedia PDF Downloads 265

Authors: Weixing Tan

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Production of nutraceuticals from microalgae—a virtually untapped natural phyto-based source of which there are 200,000 to 1,000,000 species—offers a sustainable and healthy alternative to conventionally sourced nutraceuticals for the market. Microalgae can be grown organically using only natural sunlight, water and nutrients at an extremely fast rate, e.g. 10-100 times more efficiently than crops or trees. However, the commercial success of microalgae products at scale remains limited largely due to the lack of economically viable technologies. There are two major microalgae production systems or technologies currently available: 1) the open system as represented by open pond technology and 2) the closed system such as photobioreactors (PBR). Each carries its own unique features and challenges. Although an open system requires a lower initial capital investment relative to a PBR, it conveys many unavoidable drawbacks; for example, much lower productivity, difficulty in contamination control/cleaning, inconsistent product quality, inconvenience in automation, restriction in location selection, and unsuitability for cold areas – all directly linked to the system openness and flat underground design. On the other hand, a PBR system has characteristics almost entirely opposite to the open system, such as higher initial capital investment, better productivity, better contamination and environmental control, wider suitability in different climates, ease in automation, higher and consistent product quality, higher energy demand (particularly if using artificial lights), and variable operational expenses if not automated. Although closed systems like PBRs are not highly competitive yet in current nutraceutical supply market, technological advances can be made, in particular for the PBR technology, to narrow the gap significantly. One example is a readily scalable P2P Microalgae PBR Technology at Grande Prairie Regional College, Canada, developed over 11 years considering return on investment (ROI) for key production processes. The P2P PBR system is approaching economic viability at a pre-commercial stage due to five ROI-integrated major components. They include: (1) optimum use of free sunlight through attenuation (patented); (2) simple, economical, and chemical-free harvesting (patent ready to file); (3) optimum pH- and nutrient-balanced culture medium (published), (4) reliable water and nutrient recycling system (trade secret); and (5) low-cost automated system design (trade secret). These innovations have allowed P2P Microalgae Technology to increase daily yield to 106 g/m2/day of Chlorella vulgaris, which contains 50% proteins and 2-3% omega-3. Based on the current market prices and scale-up factors, this P2P PBR system presents as a promising microalgae technology for market competitive nutraceutical supply.

Keywords: microalgae technology, nutraceuticals, open pond, photobioreactor PBR, return on investment ROI, technological advances

Procedia PDF Downloads 157

Authors: Dalia Ambrazaitienė, Monika Vilkienė, Danute Karcauskienė, Gintaras Siaudinis

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The soil is a complex ecosystem that is part of our biosphere. The ability of soil to provide ecosystem services is dependent on microbial diversity. T Tillage is one of the major factors that affect soil properties. The no-till systems or shallow ploughless tillage are opposite of traditional deep ploughing, no-tillage systems, for instance, increase soil organic matter by reducing mineralization rates and stimulating litter concentrations of the top soil layer, whereas deep ploughing increases the biological activity of arable soil layer and reduces the incidence of weeds. The role of soil organisms is central to soil processes. Although the number of microbial species in soil is still being debated, the metagenomic approach to estimate microbial diversity predicted about 2000 – 18 000 bacterial genomes in 1 g of soil. Despite the key role of bacteria in soil processes, there is still lack of information about the bacterial diversity of soils as affected by tillage practices. This study focused on metagenomic analysis of bacterial diversity in long-term experimental plots of Dystric Epihypogleyic Albeluvisols in western part of Lithuania. The experiment was set up in 2013 and had a split-plot design where the whole-plot treatments were laid out in a randomized design with three replicates. The whole-plot treatments consisted of two tillage methods - deep ploughing (22-25 cm) (DP), ploughless tillage (7-10 cm) (PT). Three subsamples (0-20 cm) were collected on October 22, 2015 for each of the three replicates. Subsamples from the DP and PT systems were pooled together wise to make two composition samples, one representing deep ploughing (DP) and the other ploughless tillage (PT). Genomic DNA from soil sample was extracted from approximately 200 mg field-moist soil by using the D6005 Fungal/Bacterial Miniprep set (Zymo Research®) following the manufacturer’s instructions. To determine bacterial diversity and community composition, we employed a culture – independent approach of high-throughput pyrosequencing of the 16S rRNA gene. Metagenomic sequencing was made with Illumina MiSeq platform in Base Clear Company. The microbial component of soil plays a crucial role in cycling of nutrients in biosphere. Our study was a preliminary attempt at observing bacterial diversity in soil under two common but contrasting tillage practices. The number of sequenced reads obtained for PT (161 917) was higher than DP (131 194). The 10 most abundant genus in soil sample were the same (Arthrobacter, Candidatus Saccharibacteria, Actinobacteria, Acidobacterium, Mycobacterium, Bacillus, Alphaproteobacteria, Longilinea, Gemmatimonas, Solirubrobacter), just the percent of community part was different. In DP the Arthrobacter and Acidobacterium consist respectively 8.4 % and 2.5%, meanwhile in PT just 5.8% and 2.1% of all community. The Nocardioides and Terrabacter were observed just in PT. This work was supported by the project VP1-3.1-ŠMM-01-V-03-001 NKPDOKT and National Science Program: The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: deep ploughing, metagenomics, ploughless tillage, soil community analysis

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Authors: Eliane Abdo, Olivier Colot

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SMEs are always considered as a national priority due to their contribution to job creation, innovation and growth. Once the start-up phase is crossed with encouraging results, the company enters the phase of growth. In order to improve its competitiveness, maintain and increase its market share, the company is in the necessity even the obligation to develop its tangible and intangible investments. SMEs are generally closed companies with special and critical financial situation, limited resources and difficulty to access the capital markets; their shareholders are always living in a conflict between their independence and their need to increase capital that leads to the entry of new shareholder. The capital structure was always considered the core of research in corporate finance; moreover, the financial crisis and its repercussions on the credit’s availability, especially for SMEs make SME financing a hot topic. On the other hand, financial theories do not provide answers to capital structure’s questions; they offer tools and mode of financing that are more accessible to larger companies. Yet, SME’s capital structure can’t be independent of their governance structure. The classic financial theory supposes independence between the investment decision and the financing decision. Thus, investment determines the volume of funding, but not the split between internal or external funds. In this context, we find interesting to study the hypothesis that SMEs respond positively to the financial theories applied to large firms and to check if they are constrained by conventional solutions used by large companies. In this context, this research focuses on the analysis of the resource’s structure of SME in parallel with their investments’ structure, in order to highlight a link between their assets and liabilities structure. We founded our conceptual model based on two main theoretical frameworks: the Pecking order theory, and the Trade Off theory taking into consideration the SME’s characteristics. Our data were generated from DIANE database. Five hypotheses were tested via a panel regression to understand the type of dependence between the financing methods of 3,244 French SMEs and the development of their investment over a period of 10 years (2007-2016). The results show dependence between equity and internal financing in case of intangible investments development. Moreover, this type of business is constraint to financial debts since the guarantees provided are not sufficient to meet the banks' requirements. However, for tangible investments development, SMEs count sequentially on internal financing, bank borrowing, and new shares issuance or hybrid financing. This is compliant to the Pecking Order Theory. We, therefore, conclude that unlisted SMEs incur more financial debts to finance their tangible investments more than their intangible. However, they always prefer internal financing as a first choice. This seems to be confirmed by the assumption that the profitability of the company is negatively related to the increase of the financial debt. Thus, the Pecking Order Theory predictions seem to be the most plausible. Consequently, SMEs primarily rely on self-financing and then go, into debt as a priority to finance their financial deficit.

Keywords: capital structure, investments, life cycle, pecking order theory, trade off theory

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Authors: Tshimangadzo Jeanette Raedani, Edgar Musie, Afsatou Traore

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Background: Street-vended meats, including chicken, pork, and beef, are popular in urban areas worldwide due to their convenience and affordability. However, these meats often pose a significant risk of foodborne diseases. The high water activity, protein content, and nearly neutral pH of meat create conditions conducive to the growth of pathogenic bacteria. Street foods, particularly meats, are frequently linked to outbreaks of foodborne illnesses due to potential contamination from improper handling and preparation. This study aimed to assess the microbial quality and safety of street-vended ready-to-eat meat sold in the Thohoyandou area. Method: The study involved collecting 168 samples of street-vended meat, split evenly between chicken (n=84) and beef (n=84), from various vendors around Thohoyandou. The samples were randomly selected and transported in sterile conditions to the Department of Food Microbiology at the University of Venda for analysis. Each 10-gram sample was cultured in selective media: MSA for Staphylococcus aureus, EMB for E. coli O157, XLD agar for Salmonella, and Sorbitol McConkey for Shigella. After initial culturing, the presumptive colonies were sub-cultured for purification and identified through Gram staining and biochemical tests, including Catalase, API 20E, Klingler Iron Agar Test, and Vitek 2 system. Antibiotic susceptibility was tested using agents such as Ampicillin, Chloramphenicol, Penicillin, Neomycin, Tetracycline, Streptomycin, and Amoxicillin. Molecular characterization was performed to identify E. coli pathotypes using multiplex PCR. Results: Out of 168 samples tested, 32 (19%) were positive for Staphylococcus spp., with the highest prevalence found in cooked chicken meat. The most common staphylococcus species identified were S. xylosus (13.2%) and S. saprophyticus (10.5%). E. coli was present in 29 (19.3%) of the samples, with the highest prevalence in fried chicken. Antibiotic susceptibility testing showed that 100% of E. coli isolates were resistant to Ampicillin, Tetracycline, and Penicillin, but 100% were susceptible to Neomycin. Staphylococcus spp. isolates were also 100% resistant to Ampicillin and 100% susceptible to Neomycin. The study detected a range of virulence genes in E. coli, with prevalence rates from 13.33% to 86.67%. The identified pathotypes included EPEC, EHEC, ETEC, EAEC, and EIEC, with many isolates showing mixed pathotypes. Conclusion: The study highlighted that the microbial quality and safety of street-vended meats in Thohoyandou are inadequate, rendering them unsafe for consumption. The presence of pathogenic microorganisms in both beef and chicken samples indicates significant risks associated with poor personal hygiene and food preparation practices. This underscores the need for improved monitoring and stricter food safety measures to prevent foodborne diseases and ensure consumer safety.

Keywords: meat, microbial analysis, street vendors, E. coli

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Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: G. Singer, M. Golan

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Providing students with learning disabilities (LD) with extra time to grant them equal access to the exam is a necessary but insufficient condition to compensate for their LD; there should also be a clear indication that the additional time was actually used. For example, if students with LD use more time than students without LD and yet receive lower grades, this may indicate that a different accommodation is required. If they achieve higher grades but use the same amount of time, then the effectiveness of the accommodation has not been demonstrated. The main goal of this study is to evaluate the effect of including parameters related to LD and extended exam time, along with other commonly-used characteristics (e.g., student background and ability measures such as high-school grades), on the ability of ordinal decision-tree algorithms to predict exam performance. We use naturally-occurring data collected from hundreds of undergraduate engineering students. The sub-goals are i) to examine the improvement in prediction accuracy when the indicator of exam performance includes 'actual time used' in addition to the conventional indicator (exam grade) employed in most research; ii) to explore the effectiveness of extended exam time on exam performance for different courses and for LD students with different profiles (i.e., sets of characteristics). This is achieved by using the patterns (i.e., subgroups) generated by the algorithms to identify pairs of subgroups that differ in just one characteristic (e.g., course or type of LD) but have different outcomes in terms of exam performance (grade and time used). Since grade and time used to exhibit an ordering form, we propose a method based on ordinal decision-trees, which applies a weighted information-gain ratio (WIGR) measure for selecting the classifying attributes. Unlike other known ordinal algorithms, our method does not assume monotonicity in the data. The proposed WIGR is an extension of an information-theoretic measure, in the sense that it adjusts to the case of an ordinal target and takes into account the error severity between two different target classes. Specifically, we use ordinal C4.5, random-forest, and AdaBoost algorithms, as well as an ensemble technique composed of ordinal and non-ordinal classifiers. Firstly, we find that the inclusion of LD and extended exam-time parameters improves prediction of exam performance (compared to specifications of the algorithms that do not include these variables). Secondly, when the indicator of exam performance includes 'actual time used' together with grade (as opposed to grade only), the prediction accuracy improves. Thirdly, our subgroup analyses show clear differences in the effect of extended exam time on exam performance among different courses and different student profiles. From a methodological perspective, we find that the ordinal decision-tree based algorithms outperform their conventional, non-ordinal counterparts. Further, we demonstrate that the ensemble-based approach leverages the strengths of each type of classifier (ordinal and non-ordinal) and yields better performance than each classifier individually.

Keywords: actual exam time usage, ensemble learning, learning disabilities, ordinal classification, time extension

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