Search results for: household accounting

Authors: Kelsey Fortin, Susan Harvey

Abstract:

The intersection between hunger and health outcomes is beginning to gain traction among the research community. With new interventions focusing on collaborations between the medical and social service sectors, this study aimed to understand the acceptability and approach of a health coaching intervention within a county-wide Midwest food pantry. Through formative research, the study used mixed methods to review secondary data and conduct surveys and semi-structured interviews with food pantry clients (n=30), staff (n=7), and volunteers (n=10). Supplemental secondary data collected and provided by pantry staff were reviewed to understand the broader pantry context of clientele health and health behaviors, annual food donations, and current pantry programming. Results from secondary data showed that the broader pantry client population reported high rates of chronic disease, low consumption of fruits and vegetables, and poor self-reported health, while annual donation data showed increases in produce availability on pantry shelves. This disconnect between produce availability, client health status, and behaviors was supported in the current study, with pantry staff and volunteers reporting lack of knowledge in produce selection and preparation being amongst the most common client inquiries and barriers to healthy food selection. Additional supports to secondary data came from pantry clients in the current study through self-reported high rates of both individual (60%, n=18) and household (43%, n=13 ) disease diagnosis, low consumption of fruits and vegetables averaging zero to one servings of vegetables (67%, n=20) and fruits (47%, n=14) per day, and low levels of physical activity averaging zero to 120 minutes per week (67%, n=20). Further, pantry clients provided health coaching programmatic recommendations through interviews with feedback such as non-judgmental coaching, accountability measures, and providing participant incentives as considerations for future program design and approach. Volunteers and staff reported the need for client education in food preparation, basic nutrition and physical activity, and the need for additional health expertise to educate and respond to diet related nutrition recommendations. All three stakeholder groups supported hosting a health coach within the pantry to focused on nutrition, physical activity, and health programming, with one client stating, 'I am hoping it really works out [the health coaching program]. I think it would be great for something like this to be offered for someone that isn’t knowledgeable like me.' In conclusion, high rates of chronic disease, partnered with low food, nutrition, and physical activity literacy among pantry clients, demonstrates the need to address health behaviors. With all three stakeholder groups showing acceptability of a health coaching program, partnered with existing literature showing health coaching success as a behavior change intervention, further research should be conducted to pilot the design and implementation of such a program in the pantry setting.

Keywords: food insecurity, formative research, food pantries, health coaching, hunger and health

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Abderrahmane Soufi

Abstract:

The building sector is the largest consumer of energy in France, accounting for 44% of French consumption. To reduce energy consumption and improve energy efficiency, France implemented an energy transition law targeting 40% energy savings by 2030 in the tertiary building sector. Building simulation tools are used to predict the energy performance of buildings but the reliability of these tools is hampered by discrepancies between the real and simulated energy performance of a building. This performance gap lies in the simplified assumptions of certain factors, such as the behavior of occupants on air conditioning and heating, which is considered deterministic when setting a fixed operating schedule and a fixed interior comfort temperature. However, the behavior of occupants on air conditioning and heating is stochastic, diverse, and complex because it can be affected by many factors. Probabilistic models are an alternative to deterministic models. These models are usually derived from statistical data and express occupant behavior by assuming a probabilistic relationship to one or more variables. In the literature, logistic regression has been used to model the behavior of occupants with regard to heating and air conditioning systems by considering univariate logistic models in residential buildings; however, few studies have developed multivariate models for higher education and vocational training buildings in a Mediterranean climate. Therefore, in this study, occupant behavior on heating and air conditioning systems was modeled using logistic regression. Occupant behavior related to the turn-on heating and air conditioning systems was studied through experimental measurements collected over a period of one year (June 2023–June 2024) in three classrooms occupied by several groups of students in engineering schools and professional training. Instrumentation was provided to collect indoor temperature and indoor relative humidity in 10-min intervals. Furthermore, the state of the heating/air conditioning system (off or on) and the set point were determined. The outdoor air temperature, relative humidity, and wind speed were collected as weather data. The number of occupants, age, and sex were also considered. Logistic regression was used for modeling an occupant turning on the heating and air conditioning systems. The results yielded a proposed model that can be used in building simulation tools to predict the energy performance of teaching buildings. Based on the first months (summer and early autumn) of the investigations, the results illustrate that the occupant behavior of the air conditioning systems is affected by the indoor relative humidity and temperature in June, July, and August and by the indoor relative humidity, temperature, and number of occupants in September and October. Occupant behavior was analyzed monthly, and univariate and multivariate models were developed.

Keywords: occupant behavior, logistic regression, behavior model, mediterranean climate, air conditioning, heating

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Authors: Tesfaldet Mekonnen Estifanos, Chen Hui, Afewerki Weldezgi

Abstract:

Background: Youth in general and young females in particular, remain at the center of the HIV/AIDS epidemic. Sexual risk-taking among young unmarried women is relatively high and are the most vulnerable and highly exposed to HIV/AIDS. Improvements in the status of HIV/AIDS knowledge and acceptance attitude towards people living with HIV (PLWHIV) plays a great role in averting the incidence of HIV/AIDS. Thus, the aim of the study was to explore the level and correlates of HIV/AIDS knowledge and accepting attitude toward PLWHIV. Methods: A cross-sectional study was conducted using data from the Uganda Demographic Health Survey 2016 (UDHS-2016). National level representative household surveys using a multistage cluster probability sampling method, face to face interviews with standard questionnaires were performed. Unmarried women aged 15-24 years with a sample size of 2019 were selected from the total sample of 8674 women aged 15-49 years and were analyzed using SPSS version 23. Independent variables such as age, religion, educational level, residence, and wealth index were included. Two binary outcome variables (comprehensive HIV/AIDS knowledge and acceptance attitude toward PLWHIV) were utilized. We used the chi-square test as well as multivariate regression analysis to explore correlations of explanatory variables with the outcome variables. The results were reported by odds ratios (OR) with 95% confidence interval (95% CI), taking a p-value less than 0.05 as significant. Results: Almost all (99.3%) of the unmarried women aged 15-24 years were aware of HIV/AIDS, but only 51.2% had adequate comprehensive knowledge on HIV/AIDS. Only 69.4% knew both methods: using a condom every time had sex, and having only one faithful uninfected partner can prevent HIV/AIDS transmission. About 66.6% of the unmarried women reject at least two common local misconceptions about HIV/AIDS. Moreover, an alarmingly few (20.3%) of the respondents had a positive acceptance attitude to PLWHIV. On multivariate analysis, age (20-24 years), living in urban, being educated and wealthier, were predictors of having adequate comprehensive HIV/AIDS knowledge. On the other hand, research participants with adequate comprehensive knowledge about HIV/AIDS were highly likely (OR, 1.94 95% CI, 1.52-2.46) to have a positive acceptance attitude to PLWHIV than those with inadequate knowledge. Respondents with no education, Muslim, and Pentecostal religion were emerged less likely to have a positive acceptance attitude to PLWHIV. Conclusion: This study found out the highly accepted level of awareness, but the knowledge and positive acceptance attitude are not encouraging. Thus, expanding access to comprehensive sexuality and strengthening educational campaigns on HIV/AIDS in communities, health facilities, and schools is needed with a greater focus on disadvantaged women having low educational level, poor socioeconomic status, and those residing in rural areas. Sexual risk behaviors among the most affected people - young women have also a role in the spread of HIV/AIDS. Hence, further research assessing the significant contributing factors for sexual risk-taking might have a positive impact on the fight against HIV/AIDS.

Keywords: acceptance attitude, HIV/AIDS, knowledge, unmarried women

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Authors: Maria Reznakova, Michala Strnadova, Lukas Reznak

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The global financial crisis that erupted in 2008 is associated mainly with the debt crisis. It quickly spread globally through financial markets, international banks and trade links, and affected many economic sectors. Measured by the index of the year-on-year change in GDP and industrial production, the consequences of the global financial crisis manifested themselves with some delay also in the Czech economy. This can be considered a result of the overwhelming export orientation of Czech industrial enterprises. These events offer an important opportunity to study how financial and macroeconomic instability affects corporate performance. Corporate performance factors have long been given considerable attention. It is therefore reasonable to ask whether the findings published in the past are also valid in the times of economic instability and subsequent recession. The decisive factor in effective corporate performance measurement is the existence of an appropriate system of indicators that are able to assess progress in achieving corporate goals. Performance measures may be based on non-financial as well as on financial information. In this paper, financial indicators are used in combination with other characteristics, such as the firm size and ownership structure. Financial performance is evaluated based on traditional performance indicators, namely, return on equity and return on assets, supplemented with indebtedness and current liquidity indices. As investments are a very important factor in corporate performance, their trends and importance were also investigated by looking at the ratio of investments to previous year’s sales and the rate of reinvested earnings. In addition to traditional financial performance indicators, the Economic Value Added was also used. Data used in the research were obtained from a questionnaire survey administered in industrial enterprises in the Czech Republic and from AMADEUS (Analyse Major Database from European Sources), from which accounting data of companies were obtained. Respondents were members of the companies’ senior management. Research results unequivocally confirmed that corporate performance dropped significantly in the 2010-2012 period, which can be considered a result of the global financial crisis and a subsequent economic recession. It was reflected mainly in the decreasing values of profitability indicators and the Economic Value Added. Although the total year-on-year indebtedness declined, intercompany indebtedness increased. This can be considered a result of impeded access of companies to bank loans due to the credit crunch. Comparison of the results obtained with the conclusions of previous research on a similar topic showed that the assumption that firms under foreign control achieved higher performance during the period investigated was not confirmed.

Keywords: corporate performance, foreign control, intercompany indebtedness, ratio of investment

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Authors: Umbreen Salim, Anila Noor

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This paper analyses the influences and faces of colonialism in women’s participation in economic activity in postcolonial Pakistan, through postcolonial feminist economic lens. It is an attempt to probe the shifts in gender inequalities that have existed in three stages; pre-colonial, colonial, and postcolonial times in the Indo-Pak subcontinent. It delves into an inquiry of pre-colonial as it is imperative to understand the situation and context before colonisation in order to assess the deviations associated with its onset. Hence, in order to trace gender inequalities this paper analyses from Mughal Era (1526-1757) that existed before British colonisation, then, the gender inequalities that existed during British colonisation (1857- 1947) and the associated dynamics and changes in women’s vulnerabilities to participate in the economy are examined. Followed by, the postcolonial (1947 onwards) scenario of discriminations and oppressions faced by women. As part of the research methodology, primary and secondary data analysis was done. Analysis of secondary data including literary works and photographs was carried out, followed by primary data collection using ethnographic approaches and participatory tools to understand the presence of coloniality and gender inequalities embedded in the social structure through participant’s real-life stories. The data is analysed using feminist postcolonial analysis. Intersectionality has been a key tool of analysis as the paper delved into the gender inequalities through the class and caste lens briefly touching at religion. It is imperative to mention the significance of the study and very importantly the practical challenges as historical analysis of 18th and 19th century is involved. Most of the available work on history is produced by a) men and b) foreigners and mostly white authors. Since the historical analysis is mostly by men the gender analysis presented misses on many aspects of women’s issues and since the authors have been mostly white European gives it as Mohanty says, ‘under western eyes’ perspective. Whereas the edge of this paper is the authors’ deep attachment, belongingness as lived reality and work with women in Pakistan as postcolonial subjects, a better position to relate with the social reality and understand the phenomenon. The study brought some key results as gender inequalities existed before colonisation when women were hidden wheel of stable economy which was completely invisible. During the British colonisation, the vulnerabilities of women only increased and as compared to men their inferiority status further strengthened. Today, the postcolonial woman lives in deep-rooted effects of coloniality where she is divided in class and position within the class, and she has to face gender inequalities within household and in the market for economic participation. Gender inequalities have existed in pre-colonial, during colonisation and postcolonial times in Pakistan with varying dynamics, degrees and intensities for women whereby social class, caste and religion have been key factors defining the extent of discrimination and oppression. Colonialism may have physically ended but the coloniality remains and has its deep, broad and wide effects in increasing gender inequalities in women’s participation in the economy in Pakistan.

Keywords: colonialism, economic participation, gender inequalities, women

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Authors: Jennifer Wright

Abstract:

The recent rise of powerful terrorist groups such as ISIS and Al-Qaeda brings up concerns about nuclear terrorism as well as a focus on nuclear security, specifically the physical security of nuclear weapons and fissile material storage sites in countries where powerful nonstate actors are present. Particularly because these non-state actors, who lack their own sovereign territory, cannot be ‘deterred’ in the traditional sense. In light of the current threat environment, it’s necessary to now rethink these strategies in the 21st century – a multipolar world with the presence of powerful non-state actors. As a country in the spotlight for its low ranking on the Nuclear Threat Initiative’s (NTI) Nuclear Security Index, Pakistan is a relevant example to explore the question of whether the presence of non-state actors poses a real risk to nuclear security today. It’s necessary to take a look at their nuclear security policies to determine if they’re robust enough to deal with political instability and violence in the country. After carrying out interviews with experts in May 2017 in Islamabad on nuclear security and nuclear terrorism, this paper aims to highlight findings by providing a Pakistan-centric view on the subject and give experts there a chance to counter criticism. Western media would have us fearful of nuclear security mechanisms in Pakistan after reports that areas such as cybersecurity and accounting and control of materials are weak, as well as sensitive nuclear material being transported in unmarked, unguarded vehicles. Also reported are cases where terrorist groups carried out targeted attacks against Pakistani military bases or secure sites where nuclear material is stored. One specific question asked of each interviewee in Islamabad was Do you feel the threat of nuclear terrorism calls into question the reliance on deterrence? Their responses will be elaborated on in the longer paper, but overall they demonstrate views that deterrence still serves a purpose for state-to-state security strategy, but not for a state in countering nonstate threats. If nuclear security is lax enough for these non-state actors to get their hands on either an intact nuclear weapon or enough military-grade fissile material to build a nuclear weapon, then what would stop them from launching a nuclear attack? As deterrence is a state-centric strategy, it doesn’t work to deter non-state actors from carrying out an attack on another state, as they lack their own territory, and as such, are not fearful of a reprisal attack. Deterrence will need to be addressed, and its relevance analyzed to determine its utility in the current security environment. The aim of this research is to demonstrate the real risk of nuclear terrorism by pointing to weaknesses in global nuclear security, particularly in Pakistan. The research also aims to provoke thought on the weaknesses of deterrence as a whole. Original thinking is needed as we attempt to adequately respond to the 21st century’s current threat environment.

Keywords: deterrence, non-proliferation, nuclear security, nuclear terrorism

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Authors: Berhanu Keno Terfa

Abstract:

Flash floods are among the most dangerous natural disasters that pose a significant threat to human existence. They occur frequently and can cause extensive damage to homes, infrastructure, and ecosystems while also claiming lives. Although flash floods can happen anywhere in the world, their impact is particularly severe in developing countries due to limited financial resources, inadequate drainage systems, substandard housing options, lack of early warning systems, and insufficient preparedness. To address these challenges, a comprehensive study has been undertaken to analyze and map flood inundation using Geographic Information System (GIS) techniques by considering various factors that contribute to flash flood resilience and developing effective mitigation strategies. Key factors considered in the analysis include slope, drainage density, elevation, Curve Number, rainfall patterns, land-use/cover classes, and soil data. These variables were computed using ArcGIS software platforms, and data from the Sentinel-2 satellite image (with a 10-meter resolution) were utilized for land-use/cover classification. Additionally, slope, elevation, and drainage density data were generated from the 12.5-meter resolution of the ALOS Palsar DEM, while other relevant data were obtained from the Ethiopian Meteorological Institute. By integrating and regularizing the collected data through GIS and employing the analytic hierarchy process (AHP) technique, the study successfully delineated flash flood hazard zones (FFHs) and generated a suitable land map for urban agriculture. The FFH model identified four levels of risk in Bishoftu City: very high (2106.4 ha), high (10464.4 ha), moderate (1444.44 ha), and low (0.52 ha), accounting for 15.02%, 74.7%, 10.1%, and 0.004% of the total area, respectively. The results underscore the vulnerability of many residential areas in Bishoftu City, particularly the central areas that have been previously developed. Accurate spatial representation of flood-prone areas and potential agricultural zones is crucial for designing effective flood mitigation and agricultural production plans. The findings of this study emphasize the importance of flood risk mapping in raising public awareness, demonstrating vulnerability, strengthening financial resilience, protecting the environment, and informing policy decisions. Given the susceptibility of Bishoftu City to flash floods, it is recommended that the municipality prioritize urban agriculture adaptation, proper settlement planning, and drainage network design.

Keywords: remote sensing, flush flood hazards, Bishoftu, GIS.

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Authors: Tursunay Vassilina, Aigerim Shibikeyeva, Adilet Sakhbek

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Research has been carried out to study the influence of modified zeolite fertilizers on the quantitative and qualitative indicators of cabbage variety Nezhenka. The use of zeolite and mineral fertilizers had a positive effect on both the yield and quality indicators of the studied crop. The maximum increase in yield from fertilizers was 16.5 t/ha. Application of both zeolite and fertilizer increased the dry matter, sugar and vitamin C content of cabbage heads. It was established that the cabbage contains an amount of nitrates that is safe for human health. Among vegetable crops, cabbage has both food and feed value. One of the limiting factors in the sale of vegetable crops is the degradation of soil fertility due to depletion of nutrient reserves and erosion processes, and non-compliance with fertilizer application technologies. Natural zeolites are used as additives to mineral fertilizers for application in the field, which makes it possible to reduce their doses to minimal quantities. Zeolites improve the agrophysical and agrochemical properties of the soil and the quality of plant products. The research was carried out in a field experiment, carried out in 3 repetitions, on dark chestnut soil in 2023. The soil (pH = 7.2-7.3) of the experimental plot is dark chestnut, the humus content in the arable layer is 2.15%, gross nitrogen 0.098%, phosphorus, potassium 0.225 and 2.4%, respectively. The object of the study was the late cabbage variety Nezhenka. Scheme for applying fertilizers to cabbage: 1. Control (without fertilizers); 2. Zeolite 2t/ha; 3. N45P45K45; 4. N90P90K90; 5. Zeolite, 2 t/ha + N45P45K45; 6. Zeolite, 2 t/ha + N90P90K90. Yield accounting was carried out on a plot-by-plot basis manually. In plant samples, the following was determined: dry matter content by thermostatic method (at 105ºC); sugar content by Bertrand titration method, nitrate content by 1% diphenylamine solution, vitamin C by titrimetric method with acid solution. According to the results, it was established that the yield of cabbage was high – 42.2 t/ha in the treatment Zeolite, 2 t/ha + N90P90K90. When determining the biochemical composition of white cabbage, it was found that the dry matter content was 9.5% and increased with fertilized treatments. The total sugar content increased slightly with the use of zeolite (5.1%) and modified zeolite fertilizer (5.5%), the vitamin C content ranged from 17.5 to 18.16%, while in the control, it was 17.21%. The amount of nitrates in products also increased with increasing doses of nitrogen fertilizers and decreased with the use of zeolite and modified zeolite fertilizer but did not exceed the maximum permissible concentration. Based on the research conducted, it can be concluded that the application of zeolite and fertilizers leads to a significant increase in yield compared to the unfertilized treatment; contribute to the production of cabbage with good and high quality indicators.

Keywords: cabbage, dry matter, nitrates, total sugar, yield, vitamin C

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Dejene Ermias Mekango, Mussie Alemayehu, Gebremedhin Berhe Gebregergs, Araya Abrha Medhanye, Gelila Goba

Abstract:

Background: Maternal near miss (MNM) can be used as a proxy indicator of maternal mortality ratio. There is a huge gap in life time risk between Sub-Saharan Africa and developed countries. In Ethiopia, a significant number of women die each year from complications during pregnancy, childbirth and the post-partum period. Besides, a few studies have been performed on MNM, and little is known regarding determinant factors. This study aims to identify determinants of MNM among women in Tigray region, Northern Ethiopia. Methods: a case-control study in hospital found in Tigray region, Ethiopia was conducted from January 30 - March 30, 2016. The sample included 103 cases and 205 controls recruited from women seeking obstetric care at six public hospitals. Clients having a life-threatening obstetric complication including haemorrhage, hypertensive diseases of pregnancy, dystocia, infections, and anemia or clinical signs of severe anemia in women without haemorrhage were taken as cases and those with normal obstetric outcomes were considered as controls. Cases were selected based on proportional to size allocation while systematic sampling was employed for controls. Data were analyzed using SPSS version 20.0. Binary and multiple variable logistic regression (odds ratio) analyses were calculated with 95% CI. Results: The largest proportion of cases and controls was among the ages of20–29 years, accounting for37.9 %( 39) of cases and 31.7 %( 65) of controls. Roughly 90% of cases and controls were married. About two-thirds of controls and 45.6 %( 47) of cases had gestational age between 37-41 weeks. History of chronic medical conditions was reported in 55.3 %(57) of cases and 33.2%(68) of controls. Women with no formal education [AOR=3.2;95%CI:1.24, 8.12],being less than 16 years old at first pregnancy [AOR=2.5; 95%CI:1.12,5.63],induced labor[AOR=3; 95%CI:1.44, 6.17], history of Cesarean section (C-section) [AOR=4.6; 95%CI: 1.98, 7.61] or chronic medical disorder[AOR=3.5;95%CI:1.78, 6.93], and women who traveled more than 60 minutes before reaching their final place of care[AOR=2.8;95% CI: 1.19,6.35] all had higher odds of experiencing MNM. Conclusions: The Government of Ethiopia should continue its effort to address the lack of road and health facility access as well as education, which will help reduce MNM. Work should also be continued to educate women and providers about common predictors of MNM like the history of C-section, chronic illness, and teenage pregnancy. These efforts should be carried out at the facility, community, and individual levels. The targeted follow-up to women with a history of chronic disease and C-section could also be a practical way to reduce MNM.

Keywords: maternal near miss, severe obstetric hemorrhage, hypertensive disorder, c-section, Tigray, Ethiopia

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Authors: Skyler Kim

Abstract:

An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Nathaniel Oladimeji Dixon, Adekemi Dorcas Fadun

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Educational managers have observed a downward trend in the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. This is evident in the low-quality service delivery of administrators and unaccomplished institutional goals and missions of higher education. Scholars have thus indicated the need for the deployment and adoption of a practice that encourages information collection and sharing among stakeholders with a view to improving service delivery and outcomes. This study examined the extent to which knowledge management correlated with the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. The study adopted the survey design. Three federal universities (the University of Ibadan, Federal University of Agriculture, Abeokuta, and Obafemi Awolowo University) were purposively selected because administrative ineffectiveness was more pronounced among non-teaching staff in government-owned universities, and these federal universities were long established. The proportional and stratified random sampling was adopted to select 1156 non-teaching staff across the three universities along the three existing layers of the non-teaching staff: secretarial (senior=311; junior=224), non-secretarial (senior=147; junior=241) and technicians (senior=130; junior=103). Knowledge Management Practices Questionnaire with four sub-scales: knowledge creation (α=0.72), knowledge utilization (α=0.76), knowledge sharing (α=0.79) and knowledge transfer (α=0.83); and Administrative Effectiveness Questionnaire with four sub-scales: communication (α=0.84), decision implementation (α=0.75), service delivery (α=0.81) and interpersonal relationship (α=0.78) were used for data collection. Data were analyzed using descriptive statistics, Pearson product-moment correlation and multiple regression at 0.05 level of significance, while qualitative data were content analyzed. About 59.8% of the non-teaching staff exhibited a low level of knowledge management. The indices of administrative effectiveness of non-teaching staff were rated as follows: service delivery (82.0%), communication (78.0%), decision implementation (71.0%) and interpersonal relationship (68.0%). Knowledge management had significant relationships with the indices of administrative effectiveness: service delivery (r=0.82), communication (r=0.81), decision implementation (r=0.80) and interpersonal relationship (r=0.47). Knowledge management had a significant joint prediction on administrative effectiveness (F (4;1151)= 0.79, R=0.86), accounting for 73.0% of its variance. Knowledge sharing (β=0.38), knowledge transfer (β=0.26), knowledge utilization (β=0.22), and knowledge creation (β=0.06) had relatively significant contributions to administrative effectiveness. Lack of team spirit and withdrawal syndrome is the major perceived constraints to knowledge management practices among the non-teaching staff. Knowledge management positively influenced the administrative effectiveness of the non-teaching staff in federal universities in South-west Nigeria. There is a need to ensure that the non-teaching staff imbibe team spirit and embrace teamwork with a view to eliminating their withdrawal syndromes. Besides, knowledge management practices should be deployed into the administrative procedures of the university system.

Keywords: knowledge management, administrative effectiveness of non-teaching staff, federal universities in the south-west of nigeria., knowledge creation, knowledge utilization, effective communication, decision implementation

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Authors: Varun Joshi, M. S. Rawat

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The Indian Himalayan Region (IHR) is inherently fragile and susceptible to landslide hazard due to its extremely weak geology, highly rugged topography and heavy monsoonal rainfall. One of the most common hazards in the IHR is landslide, and this event is particularly frequent in Himalayan states of India i.e. Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Sikkim, Manipur and Arunachal Pradesh. Landslides are mostly triggered by extreme rainfall events but the incidence increases during monsoon months (June to September). Natural slopes which are otherwise stable but they get destabilized due to anthropogenic activities like construction of various developmental activities and deforestation. These activities are required to fulfill the developmental needs and upliftment of societal status in the region. Landslides also trigger during major earthquakes and reported most observable and damaging phenomena. Studies indicate that the landslide phenomenon has increased many folds due to developmental activities in Himalayan region. Gradually increasing and devastating consequences of landslides turned into one of the most important hydro-geological hazards in Himalayan states especially in Uttarakhand and Sikkim states of India. The recent most catastrophic rainfall in June 2013 in Uttarakhand lead to colossal loss of life and property. The societal damage due to this incident is still to be recovered even after three years. Sikkim earthquake of September 2011 is witnessed for triggering of large number of coseismic landslides. The rescue and relief team faced huge problem in helping the trapped villagers in remote locations of the state due to road side blockade by landslides. The recent past incidences of landslides in Uttarakhand, as well as Sikkim states, created a new domain of research in terms of understanding the phenomena of landslide and management of disaster in such situation. Every year at many locations landslides trigger which force dwellers to either evacuate their dwelling or lose their life and property. The communication and transportation networks are also severely affected by landslides at several locations. Many times the drinking water supply disturbed and shortage of daily need household items reported during monsoon months. To minimize the severity of landslide in IHR requires in-depth research and developmental planning. For most of the areas in the present study, landslide hazard zonation is done on 1:50,000 scale. The land use planning maps on extensive basis are not available. Therefore, there is a need of large-scale landslide hazard zonation and land use planning maps. If the scientist conduct research on desired aspects and their outcome of research is utilized by the government in developmental planning then the incidents of landslide could be minimized, subsequent impact on society, life and property would be reduced. Along with the scientific research, there is another need of awareness generation in the region for stake holders and local dwellers to combat with the landslide hazard, if triggered in their location.

Keywords: coseismic, Indian Himalayan Region, landslide hazard zonation, Sikkim, societal, Uttarakhand

Procedia PDF Downloads 252

Authors: Kenechukwu Ikebuaku

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Entrepreneurship has long been offered as the panacea for poor economic growth and high rate of unemployment. Business incubation is considered an effective means for enhancing entrepreneurial actitivities while engendering socio-economic development. Information Technology Developers Entrepreneurship Accelerator (iDEA), is a software business incubation programme established by the Nigerian government as a means of boosting digital entrepreneurship activities and reducing unemployment in the country. This study assessed the contribution of iDEA Nigeria’s entrepreneurship programmes towards enhancing the capabilities of its tenants. Using the capability approach and the sustainable livelihoods approach, the study analysed iDEA programmes’ contribution towards the expansion of participants’ entrepreneurial capabilities. Apart from identifying a set of entrepreneurial capabilities from both the literature and empirical analysis, the study went further to ascertain how iDEA incubation has helped to enhance those capabilities for its tenants. It also examined digital entrepreneurship as a valued functioning and as an intermediate functioning leading to other valuable functioning. Furthermore, the study examined gender as a conversion factor in digital entrepreneurship. Both qualitative and quantitative research methods were used for the study, and measurement of key variables was made. While the entire population was utilised to collect data for the quantitative research, purposive sampling was used to select respondents for semi-structured interviews in the qualitative research. However, only 40 beneficiaries agreed to take part in the survey while 10 respondents were interviewed for the study. Responses collected from questionnaires administered were subjected to statistical analysis using SPSS. The study developed indexes to measure the perception of the respondents, on how iDEA programmes have enhanced their entrepreneurial capabilities. The Capabilities Enhancement Perception Index (CEPI) computed indicated that the respondents believed that iDEA programmes enhanced their entrepreneurial capabilities. While access to power supply and reliable internet have the highest positive deviations around mean, negotiation skills and access to customers/clients have the highest negative deviation. These were well supported by the findings of the qualitative analysis in which the participants unequivocally narrated how the resources provided by iDEA aid them in their entrepreneurial endeavours. It was also found that iDEA programmes have a significant effect on the tenants’ access to networking opportunities, both with other emerging entrepreneurs and established entrepreneurs. While assessing gender as a conversion factor, it was discovered that there was very low female participation within the digital entrepreneurship ecosystem. The root cause of this gender disparity was found in unquestioned cultural beliefs and social norms which relegate women to a subservient position and household duties. The findings also showed that many of the entrepreneurs could be considered opportunity-based entrepreneurs rather than necessity entrepreneurs, and that digital entrepreneurship is a valued functioning for iDEA tenants. With regards to challenges facing digital entrepreneurship in Nigeria, infrastructural/institutional inadequacies, lack of funding opportunities, and unfavourable government policies, were considered inimical to entrepreneurial capabilities in the country.

Keywords: entrepreneurial capabilities, unemployment, business incubators, development

Procedia PDF Downloads 241

Authors: Clement Yeboah

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Prior research concludes that environmental commitment positively drives organisational performance. Nonetheless, the nexus and conditions under which environmental commitment capabilities contribute to a firm’s performance are less understood. The purpose of this quantitative relational study was to examine the relationship between environmental commitment and 500 firms’ performances in Ghana. The researchers further seek to draw insights from the resource-based view to conceptualize environmental commitment and green procurement practices as resource capabilities to enhance firm performance. The researchers used insights from the contingent resource-based view to examine green leadership orientation conditions under which environmental commitment capability contributes to firm performance through green procurement practices. The study’s conceptual framework was tested on primary data from some firms in the Ghanaian market. PROCESS Macro was used to test the study’s hypotheses. Beyond that, green procurement practices mediated the association between environmental commitment capabilities and the firm’s performance. The study further seeks to find out whether green leadership orientation positively moderates the indirect relationship between environmental commitment capabilities and firm performance through green procurement practices. While conventional wisdom suggests that improved environmental commitment capabilities help improve a firm’s performance, this study tested this presumed relationship between environmental commitment capabilities and firm performance and provides theoretical arguments and empirical evidence to justify how green procurement practices uniquely and in synergy with green leadership orientation transform this relationship. The study results indicated a positive correlation between environmental commitment and firm performance. This result suggests that firms that prioritize environmental sustainability and demonstrate a strong commitment to environmentally responsible practices tend to experience better overall performance. This includes financial gains, operational efficiency, enhanced reputation, and improved relationships with stakeholders. The study's findings inform policy formulation in Ghana related to environmental regulations, incentives, and support mechanisms. Policymakers can use the insights to design policies that encourage and reward firms for their environmental commitments, thereby fostering a more sustainable and environmentally responsible business environment. The findings from such research can influence the design and development of educational programs in Ghana, specifically in fields related to sustainability, environmental management, and corporate social responsibility (CSR). Institutions may consider integrating environmental and sustainability topics into their business and management courses to create awareness and promote responsible practices among future business professionals. Also the study results can also promote the adoption of environmental accounting practices in Ghana. By recognizing and measuring the environmental impacts and costs associated with business activities, firms can better understand the financial implications of their environmental commitments and develop strategies for improved performance.

Keywords: firm’s performance, green procurement practice, environmental commitment, environmental management, sustainability

Procedia PDF Downloads 93

Authors: Swati Vohra

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A genuine economic and social transformation requires equal contribution and participation from both men and women; however, achieving this gender parity is a global concern. In the patriarchal societies around the world, women have been silenced, oppressed, and subjugated. Girls and women comprise half of the world’s population. This, however, must not be the lone reason for recognizing and providing equal opportunities to them. Every individual has a right to develop through opportunities without the biases of gender, caste, race, or ethnicity. The world today is confronted by pressing issues of climate change, economic crisis, violence against women and children, escalating conflicts, to name a few. Achieving gender parity is thus an essential component in meeting this wide array of challenges in order to create just, robust and inclusive societies. In 2015, The United Nation enunciated achieving 17 Sustainable Development Goals by 2030, one of which is SGD#5- Gender Equality, that is not merely a stand-alone goal. It is central to the achievement of all 17 SDG’s. Without progress on gender equality, the global community will not only fail to achieve the SDG5, but it will also lose the impetus towards achieving the broad 2030 agenda. This research is based on a hypothesis that aims to connect the targets laid by the UN under SDG#5 - 5.4 (Recognize and value unpaid care and domestic work) and 5.5 (Ensure women participation for leadership at all levels of decision-making). The study evaluates the impact of unpaid household responsibilities on women’s leadership in India. In Indian society, women have experienced a low social status for centuries, which is reflected throughout the Indian history with preference of a male child and common occurrences of female infanticides that are still prevalent in many parts of the country. Insistence on the traditional gender roles builds patriarchal inequalities into the structure of Indian society. It is argued that a burden of unpaid labor on women is placed, which narrows the opportunities and life chances women are given and the choices they are able to make, thereby shutting them from shared participation in public and economic leadership. The study investigates theoretical framework of social construction of gender, unpaid labor, challenges to women leaders and peace theorist perspective as the core components. The methodology used is qualitative research of comprehensive literature, accompanied by the data collected through interviews of representatives of women leaders from various fields within Delhi-National Capital Region (NCR). The women leaders interviewed had the privilege of receiving good education and a conducive family support; however, post marriage and children it was not the case and the social obligations weighed heavy on them. The research concludes by recommending the importance of gender-neutral parenting and education along with government ratified paternal leaves for at least six months and childcare facilities available for both the parents at workplace.

Keywords: gender equality, gender roles, peace studies, sustainable development goals, social construction, unpaid labor, women’s leadership

Procedia PDF Downloads 124

Authors: Ikechukwu Ndu

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This study examines the econometric modeling of the relation between discretionary accrual earnings management, International Financial Reporting Standards (IFRS), and certain corporate governance factors with regard to listed Nigerian non-financial firms. Although discretionary accrual earnings management is a well-known and global problem that has an adverse impact on users of the financial statements, its relationship with IFRS and corporate governance is neither adequately researched nor properly systematically investigated in Nigeria. The dearth of research in the relation between discretionary accrual earnings management, IFRS and corporate governance in Nigeria has made it difficult for academics, practitioners, government setting bodies, regulators and international bodies to achieve a clearer understanding of how discretionary accrual earnings management relates to IFRS and certain corporate governance characteristics. This is the first study to the author’s best knowledge to date that makes interesting research contributions that significantly add to the literature of discretionary accrual earnings management and its relation with corporate governance and IFRS pertaining to the Nigerian context. A comprehensive review is undertaken of the literature of discretionary total accrual earnings management, IFRS, and certain corporate governance characteristics as well as the data, models, methodologies, and different estimators used in the study. Secondary financial statement, IFRS, and corporate governance data are sourced from Bloomberg database and published financial statements of Nigerian non-financial firms for the period 2004 to 2016. The methodology uses both the total and working capital accrual basis. This study has a number of interesting preliminary findings. First, there is a negative relationship between the level of discretionary accrual earnings management and the adoption of IFRS. However, this relationship does not appear to be statistically significant. Second, there is a significant negative relationship between the size of the board of directors and discretionary accrual earnings management. Third, CEO Separation of roles does not constrain earnings management, indicating the need to preserve relationships, personal connections, and maintain bonded friendships between the CEO, Chairman, and executive directors. Fourth, there is a significant negative relationship between discretionary accrual earnings management and the use of a Big Four firm as an auditor. Fifth, including shareholders in the audit committee, leads to a reduction in discretionary accrual earnings management. Sixth, the debt and return on assets (ROA) variables are significant and positively related to discretionary accrual earnings management. Finally, the company size variable indicated by the log of assets is surprisingly not found to be statistically significant and indicates that all Nigerian companies irrespective of size engage in discretionary accrual management. In conclusion, this study provides key insights that enable a better understanding of the relationship between discretionary accrual earnings management, IFRS, and corporate governance in the Nigerian context. It is expected that the results of this study will be of interest to academics, practitioners, regulators, governments, international bodies and other parties involved in policy setting and economic development in areas of financial reporting, securities regulation, accounting harmonization, and corporate governance.

Keywords: discretionary accrual earnings management, earnings manipulation, IFRS, corporate governance

Procedia PDF Downloads 147

Authors: Benito Minjarez, Jesse Haramati, Yury Rodriguez-Yanez, Florencio Recendiz-Hurtado, Juan-Pedro Luna-Arias, Salvador Mena-Munguia

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During the last decades, the world has experienced a rapid industrialization and an expanding economy favoring a demographic boom. As a consequence, countries around the world have focused on developing new strategies related to the production of different farm products in order to meet future demands. Consequently, different strategies have been developed seeking to improve the major food products for both humans and livestock. Corn, after wheat and rice, is the third most important crop globally and is the primary food source for both humans and livestock in many regions around the globe. In addition, maize (Zea mays) is an important source of protein accounting for up to 60% of the daily human protein supply. Generally, many of the cereal grains have proteins with relatively low nutritional value, when they are compared with proteins from meat. In the case of corn, much of the protein is found in the endosperm (75 to 85%) and is deficient in two essential amino acids, lysine, and tryptophan. This deficiency results in an imbalance of amino acids and low protein content; normal maize varieties have less than half of the recommended amino acids for human nutrition. In addition, studies have shown that this deficiency has been associated with symptoms of growth impairment, anemia, hypoproteinemia, and fatty liver. Due to the fact that most of the presently available maize varieties do not contain the quality and quantity of proteins necessary for a balanced diet, different countries have focused on the research of quality protein maize (QPM). Researchers have characterized QPM noting that these varieties may contain between 70 to 100% more residues of the amino acids essential for animal and human nutrition, lysine, and tryptophan, than common corn. Several countries in Africa, Latin America, as well as China, have incorporated QPM in their agricultural development plan. Large parts of these countries have chosen a specific QPM variety based on their local needs and climate. Reviews have described the breeding methods of maize and have revealed the lack of studies on genetic and proteomic diversity of proteins in QPM varieties, and their genetic relationships with normal maize varieties. Therefore, molecular marker identification using tools such as mass spectrometry may accelerate the selection of plants that carry the desired proteins with high lysine and tryptophan concentration. To date, QPM maize lines have played a very important role in alleviating the malnutrition, and better characterization of these lines would provide a valuable nutritional enhancement for use in the resource-poor regions of the world. Thus, the objectives of this study were to identify proteins in QPM maize in comparison with a common maize line as a control.

Keywords: corn, mass spectrometry, QPM, tryptophan

Procedia PDF Downloads 293

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

Procedia PDF Downloads 89

Authors: Nkechi V. Osuji

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The use of blockchain to address the issue of climate change is increasingly a discourse among countries, industries, and stakeholders. For a long time, the European Union (EU) has been combating the issue of climate action in industries through sustainability programs. One of such programs is the EU monitoring reporting and verification (MRV) program of the EU ETS. However, the system has some key challenges and areas for improvement, which makes it inefficient. The main objective of the research is to look at how blockchain can be used to improve the inefficiency of the EU ETS program for the Danish energy industry with a focus on its monitoring and reporting framework. Applying empirical data from 13 semi-structured expert interviews, three case studies, and literature reviews, three outcomes are presented in the study. The first is on the current conditions and challenges of monitoring and reporting CO₂ emission trading. The second is putting into consideration if blockchain is the right fit to solve these challenges and how. The third stage looks at the factors that might affect the implementation of such a system and provides recommendations to mitigate these challenges. The first stage of the findings reveals that the monitoring and reporting of CO₂ emissions is a mandatory requirement by law for all energy operators under the EU ETS program. However, most energy operators are non-compliant with the program in reality, which creates a gap and causes challenges in the monitoring and reporting of CO₂ emission trading. Other challenges the study found out are the lack of transparency, lack of standardization in CO₂ accounting, and the issue of double-counting in the current system. The second stage of the research was guided by three case studies and requirement engineering (RE) to explore these identified challenges and if blockchain is the right fit to address them. This stage of the research addressed the main research question: how can blockchain be used for monitoring and reporting CO₂ emission trading in the energy industry. Through analysis of the study data, the researcher developed a conceptual private permissioned Hyperledger blockchain and elucidated on how it can address the identified challenges. Particularly, the smart contract of blockchain was highlighted as a key feature. This is because of its ability to automate, be immutable, and digitally enforce negotiations without a middleman. These characteristics are unique in solving the issue of compliance, transparency, standardization, and double counting identified. The third stage of the research presents technological constraints and a high level of stakeholder collaboration as major factors that might affect the implementation of the proposed system. The proposed conceptual model requires high-level integration with other technologies such as the Internet of Things (IoT) and machine learning. Therefore, the study encourages future research in these areas. This is because blockchain is continually evolving its technology capabilities. As such, it remains a topic of interest in research and development for addressing climate change. Such a study is a good contribution to creating sustainable practices to solve the global climate issue.

Keywords: blockchain, carbon emission trading, European Union emission trading system, monitoring and reporting

Procedia PDF Downloads 132

Authors: C. Deangeli, P. Obentaku Obenebot, O. Omwanghe

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The study focuses on the analysis of wellbore instability in rock masses affected by weakness planes. The occurrence of failure in such a type of rocks can occur in the rock matrix and/ or along the weakness planes, in relation to the mud weight gradient. In this case the simple Kirsch solution coupled with a failure criterion cannot supply a suitable scenario for borehole instabilities. Two different numerical approaches have been used in order to investigate the onset of local failure at the wall of a borehole. For each type of approach the influence of the inclination of weakness planes has been investigates, by considering joint sets at 0°, 35° and 90° to the horizontal. The first set of models have been carried out with FLAC 2D (Fast Lagrangian Analysis of Continua) by considering the rock material as a continuous medium, with a Mohr Coulomb criterion for the rock matrix and using the ubiquitous joint model for accounting for the presence of the weakness planes. In this model yield may occur in either the solid or along the weak plane, or both, depending on the stress state, the orientation of the weak plane and the material properties of the solid and weak plane. The second set of models have been performed with PFC2D (Particle Flow code). This code is based on the Discrete Element Method and considers the rock material as an assembly of grains bonded by cement-like materials, and pore spaces. The presence of weakness planes is simulated by the degradation of the bonds between grains along given directions. In general the results of the two approaches are in agreement. However the discrete approach seems to capture more complex phenomena related to local failure in the form of grain detachment at wall of the borehole. In fact the presence of weakness planes in the discontinuous medium leads to local instability along the weak planes also in conditions not predicted from the continuous solution. In general slip failure locations and directions do not follow the conventional wellbore breakout direction but depend upon the internal friction angle and the orientation of the bedding planes. When weakness plane is at 0° and 90° the behaviour are similar to that of a continuous rock material, but borehole instability is more severe when weakness planes are inclined at an angle between 0° and 90° to the horizontal. In conclusion, the results of the numerical simulations show that the prediction of local failure at the wall of the wellbore cannot disregard the presence of weakness planes and consequently the higher mud weight required for stability for any specific inclination of the joints. Despite the discrete approach can simulate smaller areas because of the large number of particles required for the generation of the rock material, however it seems to investigate more correctly the occurrence of failure at the miscroscale and eventually the propagation of the failed zone to a large portion of rock around the wellbore.

Keywords: continuous- discontinuous, numerical modelling, weakness planes wellbore, FLAC 2D

Procedia PDF Downloads 503

Authors: Abha Gupta, Deepak K. Mishra

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Food security issue in India has surrounded over availability and accessibility of cereal which is regarded as the only food group to check hunger and improve nutrition. Significance of fruits, vegetables, meat and other food products have totally been neglected given the fact that they provide essential nutrients to the body. There is a need to shift the emphasis from cereal-based approach to a more diverse diet so that aim of achieving food security may change from just reducing hunger to an overall health. This paper attempts to analyse how far dietary diversity level has been achieved across different socio-economic groups in India. For this purpose, present paper sets objectives to determine (a) percentage share of different food groups to total food expenditure and consumption by background characteristics (b) source of and preference for all food items and, (c) diversity of diet across socio-economic groups. A cross sectional survey covering 304 households selected through proportional stratified random sampling was conducted in six villages of Aligarh district of Uttar Pradesh, India. Information on amount of food consumed, source of consumption and expenditure on food (74 food items grouped into 10 major food groups) was collected with a recall period of seven days. Per capita per day food consumption/expenditure was calculated through dividing consumption/expenditure by household size and number seven. Food variety score was estimated by giving 0 values to those food groups/items which had not been eaten and 1 to those which had been taken by households in last seven days. Addition of all food group/item score gave result of food variety score. Diversity of diet was computed using Herfindahl-Hirschman index. Findings of the paper show that cereal, milk, roots and tuber food groups contribute a major share in total consumption/expenditure. Consumption of these food groups vary across socio-economic groups whereas fruit, vegetables, meat and other food consumption remain low and same. Estimation of dietary diversity show higher concentration of diet due to higher consumption of cereals, milk, root and tuber products and dietary diversity slightly varies across background groups. Muslims, Scheduled caste, small farmers, lower income class, food insecure, below poverty line and labour families show higher concentration of diet as compared to their counterpart groups. These groups also evince lower mean intake of number of food item in a week due to poor economic constraints and resultant lower accessibility to number of expensive food items. Results advocate to make a shift from cereal based diet to dietary diversity which not only includes cereal and milk products but also nutrition rich food items such as fruits, vegetables, meat and other products. Integrating a dietary diversity approach in food security programmes of the country would help to achieve nutrition security as hidden hunger is widespread among the Indian population.

Keywords: dietary diversity, food Security, India, socio-economic groups

Procedia PDF Downloads 341

Authors: Waqas Ahmed Khan, Faheem Khokhaar

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Air pollution is one of the main perpetrators of climate change. GHGs cause melting of glaciers and cause change in temperature and heavy rain fall many gasses like Formaldehyde is not direct precursor that damage ozone like CO2 or Methane but Formaldehyde (HCHO) form glyoxal (CHOCHO) that has effect on ozone. Countries around the globe have unique air quality monitoring protocols to describe local air pollution. Formaldehyde is a colorless, flammable, strong-smelling chemical that is used in building materials and to produce many household products and medical preservatives. Formaldehyde also occurs naturally in the environment. It is produced in small amounts by most living organisms as part of normal metabolic processes. Pakistan lacks the monitoring facilities on larger scale to measure the atmospheric gasses on regular bases. Formaldehyde is formed from Glyoxal and effect mountain biodiversity and livelihood. So its monitoring is necessary in order to maintain and preserve biodiversity. Objective: Present study is aimed to measure atmospheric HCHO vertical column densities (VCDs) obtained from ground-base and compute HCHO data in Punjab and elevated areas (Rawalpindi & Islamabad) by satellite observation during the time period of 2014-2015. Methodology: In order to explore the spatial distributing of H2CO, various fields campaigns including international scientist by using car Max-Doas. Major focus was on the cities along national highways and industrial region of Punjab Pakistan. Level 2 data product of satellite instruments OMI retrieved by differential optical absorption spectroscopy (DOAS) technique are used. Spatio-temporal distribution of HCHO column densities over main cities and region of Pakistan has been discussed. Results: Results show the High HCHO column densities exceeding permissible limit over the main cities of Pakistan particularly the areas with rapid urbanization and enhanced economic growth. The VCDs value over elevated areas of Pakistan like Islamabad, Rawalpindi is around 1.0×1016 to 34.01×1016 Molecules’/cm2. While Punjab has values revolving around the figure 34.01×1016. Similarly areas with major industrial activity showed high amount of HCHO concentrations. Tropospheric glyoxal VCDs were found to be 4.75 × 1015 molecules/cm2. Conclusion: Results shows that monitoring site surrounded by Margalla hills (Islamabad) have higher concentrations of Formaldehyde. Wind data shows that industrial areas and areas having high economic growth have high values as they provide pathways for transmission of HCHO. Results obtained from this study would help EPA, WHO and air protection departments in order to monitor air quality and further preservation and restoration of mountain biodiversity.

Keywords: air quality, formaldehyde, Max-Doas, vertical column densities (VCDs), satellite instrument, climate change

Procedia PDF Downloads 214

Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

Procedia PDF Downloads 111

Authors: Alexander Otchere Fianko, Clement Yeboah, Evans Oteng

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Prior research concludes that Green Procurement Practices positively drive Organisational Performance. Nonetheless, the nexus and conditions under which Green Procurement Practices contribute to a Firm’s Performance are less understood. The purpose of this quantitative relational study was to examine the relationship between Green Procurement Practices and 500 Firms’ Performances in Ghana. The researchers further seek to draw insights from the resource-based view to conceptualize Green Procurement Practices and Environmental Commitment as resource capabilities to enhance Firm Performance. The researchers used insights from the contingent resource-based view to examine Green Leadership Orientation conditions under which Green Procurement Practices contribute to Firm Performance through Environmental Commitment Capabilities. The study’s conceptual framework was tested on primary data from some firms in the Ghanaian market. PROCESS Macro was used to test the study’s hypotheses. Beyond that, Environmental Commitment Capabilities mediated the association between Green Procurement Practices and the Firm’s Performance. The study further seeks to find out whether Green Leadership Orientation positively moderates the indirect relationship between Green Procurement Practices and Firm Performance through Environmental Commitment Capabilities. While conventional wisdom suggests that improved Green Procurement Practices help improve a Firm’s Performance, this study tested this presumed relationship between Green Procurement Practices and Firm Performance and provides theoretical arguments and empirical evidence to justify how Environmental Commitment Capabilities uniquely and in synergy with Green Leadership Orientation transform this relationship. The study results indicated a positive correlation between Green Procurement Practices and Firm Performance. This result suggests that firms that prioritize environmental sustainability and demonstrate a strong commitment to environmentally responsible practices tend to experience better overall performance. This includes financial gains, operational efficiency, enhanced reputation, and improved relationships with stakeholders. The study's findings inform policy formulation in Ghana related to environmental regulations, incentives, and support mechanisms. Policymakers can use the insights to design policies that encourage and reward firms for their Green Procurement Practices, thereby fostering a more sustainable and environmentally responsible business environment. The findings from such research can influence the design and development of educational programs in Ghana, specifically in fields related to sustainability, environmental management, and corporate social responsibility (CSR). Institutions may consider integrating environmental and sustainability topics into their business and management courses to create awareness and promote responsible practices among future business professionals. Also, the study results can also promote the adoption of environmental accounting practices in Ghana. By recognizing and measuring the environmental impacts and costs associated with business activities, firms can better understand the financial implications of their Green Procurement Practices and develop strategies for improved performance.

Keywords: environmental commitment, firm’s performance, green procurement practice, green leadership orientation

Procedia PDF Downloads 84

Authors: Nilam Bano, Uzma Iram

Abstract:

Globally, the dilemma of undernutrition has become a notable concern for the researchers, academicians, and policymakers because of its severe consequences for many centuries. The nutritional deficiencies create hurdles for the people to achieve goals related to live a better lifestyle. Not only at micro level but also at the macro level, the consequences of undernutrition affect the economic progress of the country. The initial five years of a child’s life are considered critical for the physical growth and brain development. In this regard, children require special care and good quality food (nutrient intake) to fulfill their nutritional demand of the growing body. Having the sensitive stature and health, children specially under the age of 5 years are more vulnerable to the poor economic, housing, environmental and other social conditions. Beside confronting economic challenges and political upheavals, Pakistan is also going through from a rough patch in the context of social development. Majority of the children are facing serious health problems in the absence of required nutrition. The complexity of this issue is getting severe day by day and specially children are left behind with different type of immune problems and vitamins and mineral deficiencies. It is noted that children from the well-off background are less likely affected by the undernutrition. In order to underline this issue, the present study aims to highlight the existing nutritional inequalities among the children of under five years in Pakistan. Moreover, this study strives to decompose those factors that severely affect the existing nutritional inequality and standing in the queue to capture the consideration of concerned authorities. Pakistan Demographic and Health Survey 2012-13 was employed to assess the relevant indicators of undernutrition such as stunting, wasting, underweight and associated socioeconomic factors. The objectives were executed through the utilization of the relevant empirical techniques. Concentration indices were constructed to measure the nutritional inequalities by utilizing three measures of undernutrition; stunting, wasting and underweight. In addition to it, the decomposition analysis following the logistic regression was made to unfold the determinants that severely affect the nutritional inequalities. The negative values of concentration indices illustrate that children from the marginalized background are affected by the undernutrition more than their counterparts who belong from rich households. Furthermore, the result of decomposition analysis indicates that child age, size of a child at birth, wealth index, household size, parents’ education, mother’s health and place of residence are the most contributing factors in the prevalence of existing nutritional inequalities. Considering the result of the study, it is suggested to the policymakers to design policies in a way so that the health sector of Pakistan can stimulate in a productive manner. Increasing the number of effective health awareness programs for mothers would create a notable difference. Moreover, the education of the parents must be concerned by the policymakers as it has a significant association with the present research in terms of eradicating the nutritional inequalities among children.

Keywords: concentration index, decomposition analysis, inequalities, undernutrition, Pakistan

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Olivier Mills, Bernard McDonell, Laura A. S. MacDonald

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The increasing availability and quality of internet access throughout the developing world provides an opportunity to utilize online spaces to disseminate water, sanitation and hygiene (WASH) knowledge to practitioners. Since 2001, CAWST has provided in-person education, training and consulting services to thousands of WASH practitioners all over the world, supporting them to start, troubleshoot, improve and expand their WASH projects. As CAWST continues to grow, the organization faces challenges in meeting demand from clients and in providing consistent, timely technical support. In 2012, CAWST began utilizing online spaces to expand its reach by developing a series of resources websites and webinars. CAWST has developed a WASH Education and Training resources website, a Biosand Filter (BSF) Knowledge Base, a Household Water Treatment and Safe Storage Knowledge Base, a mobile app for offline users, a live chat support tool, a WASH e-library, and a series of webinar-style online training sessions to complement its in-person capacity development services. In order to determine the preliminary outcomes of providing these online services, CAWST has monitored and analyzed registration to the online spaces, downloads of the educational materials, and webinar attendance; as well as conducted user surveys. The purpose of this analysis was to find out who was using the online spaces, where users came from, and how the resources were being used. CAWST’s WASH Resources website has served over 5,800 registered users from 3,000 organizations in 183 countries. Additionally, the BSF Knowledge Base has served over 1000 registered users from 68 countries, and over 540 people from 73 countries have attended CAWST’s online training sessions. This indicates that the online spaces are effectively reaching a large numbers of users, from a range of countries. A 2016 survey of the Biosand Filter Knowledge Base showed that approximately 61% of users are practitioners, and 39% are either researchers or students. Of the respondents, 46% reported using the BSF Knowledge Base to initiate a BSF project and 43% reported using the information to train BSF technicians. Finally, 61% indicated they would like even greater support from CAWST’s Technical Advisors going forward. The analysis has provided an encouraging indication that CAWST’s online spaces are contributing to its objective of engaging and supporting WASH practitioners to start, improve and expand their initiatives. CAWST has learned several lessons during the development of these online spaces, in particular related to the resources needed to create and maintain the spaces, and respond to the demand created. CAWST plans to continue expanding its online spaces, improving user experience of the sites, and involving new contributors and content types. Through the use of online spaces, CAWST has been able to increase its global reach and impact without significantly increasing its human resources by connecting WASH practitioners with the information they most need, in a practical and accessible manner. This paper presents on CAWST’s use of online spaces through the CAWST-developed platforms discussed above and the analysis of the use of these platforms.

Keywords: education and training, knowledge sharing, online resources, water and sanitation

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Authors: Saul Estrin, Ute Stephan, Suncica Vujic

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Background and research question: Gender differences in pay are present at all organisational levels, including at the very top. One possible way for women to circumvent organizational norms and discrimination is to engage in entrepreneurship because, as CEOs of their own organizations, entrepreneurs largely determine their own pay. While commercial entrepreneurship plays an important role in job creation and economic growth, social entrepreneurship has come to prominence because of its promise of addressing societal challenges such as poverty, social exclusion, or environmental degradation through market-based rather than state-sponsored activities. This opens the research question whether social entrepreneurship might be a form of entrepreneurship in which the pay of men and women is the same, or at least more similar; that is to say there is little or no gender pay gap. If the gender gap in pay persists also at the top of social enterprises, what are the factors, which might explain these differences? Methodology: The Oaxaca-Blinder Decomposition (OBD) is the standard approach of decomposing the gender pay gap based on the linear regression model. The OBD divides the gender pay gap into the ‘explained’ part due to differences in labour market characteristics (education, work experience, tenure, etc.), and the ‘unexplained’ part due to differences in the returns to those characteristics. The latter part is often interpreted as ‘discrimination’. There are two issues with this approach. (i) In many countries there is a notable convergence in labour market characteristics across genders; hence the OBD method is no longer revealing, since the largest portion of the gap remains ‘unexplained’. (ii) Adding covariates to a base model sequentially either to test a particular coefficient’s ‘robustness’ or to account for the ‘effects’ on this coefficient of adding covariates might be problematic, due to sequence-sensitivity when added covariates are correlated. Gelbach’s decomposition (GD) addresses latter by using the omitted variables bias formula, which constructs a conditional decomposition thus accounting for sequence-sensitivity when added covariates are correlated. We use GD to decompose the differences in gaps of pay (annual and hourly salary), size of the organisation (revenues), effort (weekly hours of work), and sources of finances (fees and sales, grants and donations, microfinance and loans, and investors’ capital) between men and women leading social enterprises. Database: Our empirical work is made possible by our collection of a unique dataset using respondent driven sampling (RDS) methods to address the problem that there is as yet no information on the underlying population of social entrepreneurs. The countries that we focus on are the United Kingdom, Spain, Romania and Hungary. Findings and recommendations: We confirm the existence of a gender pay gap between men and women leading social enterprises. This gap can be explained by differences in the accumulation of human capital, psychological and social factors, as well as cross-country differences. The results of this study contribute to a more rounded perspective, highlighting that although social entrepreneurship may be a highly satisfying occupation, it also perpetuates gender pay inequalities.

Keywords: Gelbach’s decomposition, gender gap, returns to social entrepreneurship, values and preferences

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