Saving Behavior of Women Entrepreneurs in Addis Ababa, Ethiopia

This study tried to analyze determinants of saving behavior and the decision to save of women entrepreneurs engaged in micro and small enterprises (MSE) in Addis Ababa. Descriptive statistics and the Tobit model were used to analyze data collected from 500 respondents working in 6 Woredas of Addis Ababa. The findings of the descriptive analysis showed that the mean annual savings were found to be 7894.32 birr out of the mean annual income of 32461.9 birr for the year 2019. Average propensity to save is 0.24 birr. Moreover, lack of market for products or services, lack of sufficient working capital, and inappropriate working place are the main challenges of saving which faced women entrepreneurs. From the Tobit model econometrics, the number of workers, annual income, enterprise types, and access to credit, access to market, and age of business, are statistically significant determinants of the amount of saving and the decision to save. The marginal effects after the Tobit result also indicate that the predicted value of the dependent variable (amount of saving) among savers is about 9140.61birr and the likelihood of women to save is about 65.5%. Therefore, the findings of the study imply that strong and consistent support from the government ,widening alternative sources of finance, improve working areas, training, and building a market network with consumers and producers will play an important role to enhance saving behavior and the decision to save of women entrepreneurs in Addis Ababa Keywords: Women entrepreneur, saving, Tobit model, saving determinant, Addis Ababa DOI: 10.7176/JESD/12-20-01 Publication date:October 31st 202

A RANDOMIZED PILOT TRIAL ASSESSING A BEHAVIORAL ECONOMIC SUPPLEMENT IN ALCOHOL USE DISORDER TREATMENT

Objective. Behavioral economic (BE) research has demonstrated that increasing the salience of delayed substance-free rewards increases individuals capacity for delaying gratification and allocating behavior towards larger, delayed rewards rather than smaller more immediate reward such as alcohol use. This study aimed to improve the efficacy of outpatient alcohol use disorder (AUD) treatment by adding elements that target BE mechanisms of change. The study hypothesized that the Substance-free Activity Session (SFAS) intervention will reduce alcohol use, alcohol-related problems, relative reinforcement from alcohol use, and increase future orientation compared to an active control at 3-month follow-up. Method. Participants were 41 adults engaged in AUD treatments (all met DSM-5 diagnostic criteria for AUD) at community based outpatient treatment facilities. Following baseline assessment, participants were randomized to either an individual single-session intervention focused on increasing engagement in substance-free activities and future orientation (SFAS) or to an individual sleep hygiene and nutrition education (SHyNE) control condition. Both groups received four weekly text-message reminders of the contents of the session. Participants (68.3% male; 70.7% Caucasian, M age = 38.75, SD = 13.56) reported 27.44 (SD = 14.25) binge drinking episodes in the past 90-days and 9.31 (SD = 6.62) drinks per drinking day at baseline. Results. A series of regression models (negative binomial hurdle and linear regression) that controlled for baseline levels of the outcome indicated that SFAS participants reported fewer binge drinking episodes, and reduced proportionate substance-related (relative to substance-free) reinforcement compared to controls. Further, contrary to our hypothesis, the SFAS condition was associated with less reductions of alcohol-related problems at 3-month follow-up compared to controls. Results did not indicate group differences in future orientation. SFAS participants reported high average session satisfaction ratings 9.08 (SD = .94, on a scale of 1-10). Conclusion. These preliminary pilot study results support the feasibility and acceptability of supplementing already existing outpatient AUD treatment with a single-session intervention plus remote delivery of booster contacts aimed at targeting behavioral economic elements of change. The efficacy results were ambiguous but suggest that the SFAS warrants further study as a potential means of enhancing alcohol treatment efficacy

Evaluation of the efficiency of standard assessment for Category C Taxpayers in Ethiopia: the case of Tigray Regional State

This article evaluates the application and efficiency of the Ethiopian standard tax assessment, as enshrined in the Income Tax Regulation No. 78/2002, against the tax liability of Category C Taxpayers, commonly known as small business taxpayers, referring to the practice in Eastern Zone Administration of the Tigray National Regional State. This mode of tax assessment was introduced to ensure the basic principles of tax systems such as equitability, efficiency, certainty, simplicity etc; as opposed to the situation when the tax regime is employing estimated tax assessment for the same purpose. It is found that there is a contradiction between the rules of standard tax assessment and their practical application, since the actual tax liability of the large section of the Category C Taxpayers is being assessed according to estimated taxation and this practice is incurring higher cost of administration. This article argues that the practical assessment of tax liability of Category C Taxpayers is not ensuring efficiency and the practice has to conform to the rules of standard tax assessment to meet efficiency; yet the criteria for categorization of taxpayers into Category C Taxpayers must be revised to fit the actual incomes of taxpayers to ensure equity and equality.Keywords: Category C, Efficiency, Ethiopia, Presumptive taxation, Standard assessment, Taxpayers, Tigra

Network Traffic Analysis Framework For Cyber Threat Detection

The growing sophistication of attacks and newly emerging cyber threats requires advanced cyber threat detection systems. Although there are several cyber threat detection tools in use, cyber threats and data breaches continue to rise. This research is intended to improve the cyber threat detection approach by developing a cyber threat detection framework using two complementary technologies, search engine and machine learning, combining artificial intelligence and classical technologies. In this design science research, several artifacts such as a custom search engine library, a machine learning-based engine and different algorithms have been developed to build a new cyber threat detection framework based on self-learning search and machine learning engines. Apache Lucene.Net search engine library was customized in order to function as a cyber threat detector, and Microsoft ML.NET was used to work with and train the customized search engine. This research proves that a custom search engine can function as a cyber threat detection system. Using both search and machine learning engines in the newly developed framework provides improved cyber threat detection capabilities such as self-learning and predicting attack details. When the two engines run together, the search engine is continuously trained by the machine learning engine and grow smarter to predict yet unknown threats with greater accuracy. While customizing the search engine to function as a cyber threat detector, this research also identified and proved the best algorithms for the search engine based cyber threat detection model. For example, the best scoring algorithm was found to be the Manhattan distance. The validation case study also shows that not every network traffic feature makes an equal contribution to determine the status of the traffic, and thus the variable-dimension Vector Space Model (VSM) achieves better detection accuracy than n-dimensional VSM. Although the use of different technologies and approaches improved detection results, this research is primarily focused on developing techniques rather than building a complete threat detection system. Additional components such as those that can track and investigate the impact of network traffic on the destination devices make the newly developed framework robust enough to build a comprehensive cyber threat detection appliance

WEATHERING THE STORM: THE JOURNEY OF HEALING FROM SEXUAL TRAUMA

Individuals identifying as members of an underrepresented group face a higher risk of sexual violence (RAINN, 2020; Rosay, 2016; Smith et al., 2017). Encountering sexual violence is associated with physical and mental health issues that impact the wellbeing of survivors. Developing a theory to explain the healing responses to sexual trauma helps both survivors and those providing support gain knowledge about potentially transferable healing strategies. This grounded theory study was guided by a central question: what is the experience and process of surviving sexual trauma for individuals in underrepresented groups? Six adult survivors of sexual trauma identifying as members of an underrepresented group based on their gender identity, sexual orientation, racial identity, and disability identity were interviewed in two rounds. Results showed that survivors’ journey of healing from sexual trauma included the cycles of somatic, emotional, psychological, and behavioral responses. Social support in naming, normalizing and validating survivors’ experience helped them make a positive shift in their understanding of consent and name the sexual encounter as violence. Victim questioning, on the other hand, resulted in negative trauma responses prolonging the opportunity of experiencing internal moments of relief. Survivors’ ability to shift internalized blame to externalized blame had a critical role in their intentional attunement to healing responses. Moments of relief, both internal and external, were significant to helping survivors remain afloat as they weathered the recovery storm. Survivors identified their sociocultural contexts and socialization as foundational factors that shaped the power and privilege held by the survivors and their aggressors and that impacted their identity exploration and formation. The exploration and formation of their intersecting identities has helped participants to integrate their experience of sexual trauma into their authentic self, a healing response to sexual trauma. This grounded theory provides a framework to illustrate healing strategies from sexual trauma

Effect of Soil Acidity on Nutrient Availability and Phytohormonal Responses: A Review

More than half (52%) of all fertile and productive soils worldwide are currently considered to be degraded by various factors. Among those factors, soil acidification is a very important issue. About 70% of the potential arable land and 30 % of the total land area experience some degree of soil acidity. There are several reasons why soil becomes acidic, but rainfall and leaching, acidic parent material, harvesting of high yielding crops, improper nitrogen fertilizer application, and organic matter decays are the principal ones. Acid soil affects plant growth, development and production in a number of ways. In one way, it reduces plant productivity by introducing several toxicities like Al3+, Mn2+, and H+ and in another way it affects nutrient availability primarily by altering the form of nutrients in the soil. Major plant nutrients including N, P, K, S, Ca, and Mg, and trace elements like Mo are less readily available in it and may be insufficient to support plant growth and development. Not only plants the functioning of soil microbes is also impaired by acidic conditions. Most microbial functions, such as the decomposition of organic matter and the cycling of nutrients are reduced in it. As a result, it greatly reduces the pace at which nutrients are mineralized by soil microbes into plant-available forms, potentially reducing plant absorption. Significantly, it can prevent the establishment of symbiosis and legume nodulation. Plants attempted to withstand all the effects of acid soil by exhibiting a variety of morphological and physiological responses. Mainly they tried to acclimate and adapt by altering the biosynthesis and action of phytohormones. Keywords: acid soil; nutrient availability; effects of acid soils; phytohormones DOI: 10.7176/JBAH/13-11-03 Publication date:July 31st 202

The Potential Economic Benefits of Gifaataa Celebration of Wolaita

This study was intended to explore the potential economic benefits of 'Gifaataa' Celebration of Wolaita (GCW). The subjects used were 600 individuals selected by availability sampling and 12 elders selected by purposive sampling (by their deep knowledge of overall indigenous wisdom of Wolaita) from six selected Woredas of Wolaita Zone. The descriptive research design was used having the quantitative and qualitative data collected through questionnaire, face-to-face interview and FGD. The analysis was made using the eclectic approach of data analysis. The result indicated that GCW has various potential economic benefits: It facilitates the promotion and marketing of indigenous local products and handcrafts of Wolaita. It is a fertile venture for budgetary decisions for development by local, regional and national administrators and from the attendants as a form of fund-raising. Gifaataa is also considered as an opportunity for promoting saving culture in Wolaita. However, Wolaitas have not yet exploited this potential opportunity due to lack of awareness. Based on these findings, therefore, Wolaitas should work hard to assure the sustainability of their Gifaataa celebration, the concerned government bodies should play their own roles in cultivating and transferring Gifaataa celebration to the next generation and researches of pertinent depth should be conducted by professionals for the reasons why Wolaitas have not yet exploited the potential economic benefits of their Gifaataa celebration. Keywords: Wolaita, Gifaataa, economic benefits, celebration, event-marketin

Optical Character Recognition of Amharic Documents

In Africa around 2,500 languages are spoken. Some of these languages have their own indigenous scripts. Accordingly, there is a bulk of printed documents available in libraries, information centers, museums and offices. Digitization of these documents enables to harness already available information technologies to local information needs and developments. This paper presents an Optical Character Recognition (OCR) system for converting digitized documents in local languages. An extensive literature survey reveals that this is the first attempt that report the challenges towards the recognition of indigenous African scripts and a possible solution for Amharic script. Research in the recognition of African indigenous scripts faces major challenges due to (i) the use of large number characters in the writing and (ii) existence of large set of visually similar characters. In this paper, we propose a novel feature extraction scheme using principal component and linear discriminant analysis, followed by a decision directed acyclic graph based support vector machine classifier. Recognition results are presented on real-life degraded documents such as books, magazines and newspapers to demonstrate the performance of the recognizer