Effectiveness of Inventory Control Methods in Improving Efficiency In Beverage Industry: A Case Study of Coastal Bottlers Ltd Mombasa, Kenya

This study aims to assessing the effectiveness of inventory control methods in increasing efficiency in the beverage industry. The selected case study is the COASTAL BOTTLERS Ltd, a regional processing plant that produces packages and distributes COCA COLA brands, soft drinks in the entire coast region and neighboring district. The study identifies objectives, which focus on identifying the inventory methods employed by the COASTAL BOTTLERS ltd, identifying problems encountered as a result of using these methods, and finally suggesting ways of improving inventory methods in order to improve the company’s efficiency and profitability. Inventory management has become a source of competitive advantage in recent year; good inventory management can increase efficiency of operations and profitability. By employing good inventory management techniques, companies can have low stock-outs, which means that the customers orders are fulfilled on time and this increases customer loyalty which in turn increase the sales of company. In addition, good inventory management ensures that the company spends less on warehousing and reduces the chances of goods getting spoilt in the stores. With good inventory system, it will be quick to trace items in the warehouse and ensures that less space is used to store good, this reduces cost. In addition automated inventory reduces the need for more staff in stores. All this contribute to saving costs of operations and increased profitability. Therefore, good inventory method improves efficiency. The study used a case study technique. Three types of questionnaires were designed; questionnaires for the employees, questionnaires for the vendor, and the questionnaire for the consumers. This was complimented with observation and interviews. The study was carried out in Magongo, Mikindani area and the Coastal Bottlers plant in Mombasa. In addition descriptive statistics was used to analyze the data, this included use of pie charts, bar charts, and histograms. The findings showed that the company employs a hybrid approach in its inventory control, the main emphasis is on a pull model where it uses just in time and KANBAN inventory control method, and it also employs economic order quantity and materials requirement planning. The main triggers of restocking are stock-outs and departmental requisition. COASTAL BOTTLERS Ltd has a high frequency of stock-outs; stock-outs are the major indicators of effectiveness of inventory control methods. This means that the consumers’ orders are not fulfilled on time and popular brands are always hard to find in the market. These is caused by poor inventory system in the companies operations. The phenomenon of poor inventory control method could endanger the company and cause the company to loss its customers and its market share. The company should develop a comprehensive inventory control policy, train its staff on the importance of coordination among departments. Another area of training should be on customer care management and market intelligence so as to improve market responsiveness

Progress and experiences of implementing an integrated disease surveillance and response system in Somalia; 2016–2023

IntroductionIn 2021, a regional strategy for integrated disease surveillance was adopted by member states of the World Health Organization Eastern Mediterranean Region. But before then, member states including Somalia had made progress in integration of their disease surveillance systems. We report on the progress and experiences of implementing an integrated disease surveillance and response system in Somalia between 2016 and 2023.MethodsWe reviewed 20 operational documents and identified key integrated disease surveillance and response system (IDSRS) actions/processes implemented between 2016 and 2023. We verified these through an anonymized online survey. The survey respondents also assessed Somalia’s IDSRS implementation progress using a standard IDS monitoring framework Finally, we interviewed 8 key informants to explore factors to which the current IDSRS implementation progress is attributed.ResultsBetween 2016 and 2023, 7 key IDSRS actions/processes were implemented including: establishment of high-level commitment; development of a 3-year operational plan; development of a coordination mechanism; configuring the District Health Information Software to support implementation among others. IDSRS implementation progress ranged from 15% for financing to 78% for tools. Reasons for the progress were summarized under 6 thematic areas; understanding frustrations with the current surveillance system; the opportunity occasioned by COVID-19; mainstreaming IDSRS in strategic documents; establishment of an oversight mechanism; staggering implementation of key activities over a reasonable length of time and being flexible about pre-determined timelines.DiscussionFrom 2016 to 2023, Somalia registered significant progress towards implementation of IDSRS. The 15 years of EWARN implementation in Somalia (since 2008) provided a strong foundation for IDSRS implementation. If implemented comprehensively, IDSRS will accelerate country progress toward establishment of IHR core capacities. Sustainable funding is the major challenge towards IDSRS implementation in Somalia. Government and its partners need to exploit feasible options for sustainable investment in integrated disease surveillance and response

Effectiveness of Inventory Control Methods in Improving Efficiency In Beverage Industry: A Case Study of Coastal Bottlers Ltd Mombasa, Kenya

This study aims to assessing the effectiveness of inventory control methods in increasing efficiency in the beverage industry. The selected case study is the COASTAL BOTTLERS Ltd, a regional processing plant that produces packages and distributes COCA COLA brands, soft drinks in the entire coast region and neighboring district. The study identifies objectives, which focus on identifying the inventory methods employed by the COASTAL BOTTLERS ltd, identifying problems encountered as a result of using these methods, and finally suggesting ways of improving inventory methods in order to improve the company’s efficiency and profitability. Inventory management has become a source of competitive advantage in recent year; good inventory management can increase efficiency of operations and profitability. By employing good inventory management techniques, companies can have low stock-outs, which means that the customers orders are fulfilled on time and this increases customer loyalty which in turn increase the sales of company. In addition, good inventory management ensures that the company spends less on warehousing and reduces the chances of goods getting spoilt in the stores. With good inventory system, it will be quick to trace items in the warehouse and ensures that less space is used to store good, this reduces cost. In addition automated inventory reduces the need for more staff in stores. All this contribute to saving costs of operations and increased profitability. Therefore, good inventory method improves efficiency. The study used a case study technique. Three types of questionnaires were designed; questionnaires for the employees, questionnaires for the vendor, and the questionnaire for the consumers. This was complimented with observation and interviews. The study was carried out in Magongo, Mikindani area and the Coastal Bottlers plant in Mombasa. In addition descriptive statistics was used to analyze the data, this included use of pie charts, bar charts, and histograms. The findings showed that the company employs a hybrid approach in its inventory control, the main emphasis is on a pull model where it uses just in time and KANBAN inventory control method, and it also employs economic order quantity and materials requirement planning. The main triggers of restocking are stock-outs and departmental requisition. COASTAL BOTTLERS Ltd has a high frequency of stock-outs; stock-outs are the major indicators of effectiveness of inventory control methods. This means that the consumers’ orders are not fulfilled on time and popular brands are always hard to find in the market. These is caused by poor inventory system in the companies operations. The phenomenon of poor inventory control method could endanger the company and cause the company to loss its customers and its market share. The company should develop a comprehensive inventory control policy, train its staff on the importance of coordination among departments. Another area of training should be on customer care management and market intelligence so as to improve market responsiveness

Knowledge, Attitude, and Practice Towards COVID-19 Among Abudwak Population, Galmudug, Somalia

The objective of this study is to assess the knowledge, attitude and practice towards COVID-19 among Abudwak Population in Somalia. Cross-sectional study was conducted in this study. Total of 420 participants (214 male and 206 female) were enrolled and analyzed using SPSS version 20. The knowledge of study participants were good and have clear concept of COVID-19 pandemic. Most of the respondent 184 (45%) have heard COVID-19 from social media as the main source of the knowledge. The majority of participant 342(81.4%) has good knowledge the way of transmit of COVID-19. In term of attitude mean score of the respondent their age group &gt;40 years (3.41 16?"&gt; 1.24) were higher than the respondent age group &lt; 25 years (2.98 16?"&gt; 1.14). In the case of month income, income group &gt;800 per month have practice scores (4.45 16?"> 1.25) which is higher than to the income group <200 per month (3.91 16?"&gt; 1.16). It is suggested that community should continue to strengthen the knowledge, attitude, and practice towards against the COVID-19 or any new emerging infectious disease, so that Somalia can win the battle against the disease. Keynote: COVID-19, Knowledge, Attitude, Practice, Abudwak Population. DOI: 10.7176/JHMN/96-03 Publication date: December 31st 2021

Collecting Targeted Information About Covid-19 From Research Papers By Asking Questions Based On Natural Language Processing

In the general framework of knowledge discovery, different techniques were used for information extraction from multi-label documents. As the world is currently facing COVID-19, it has made it more important than ever to have such knowledge extraction from previous documents. Therefore, Natural Language Processing (NLP) can be an essential model for tackling such an issue. By taking into consideration that having such a model plays an essential role to generate new insights in support of the ongoing fight against this infectious disease. This work introduces a sophisticated model that is able to read data from various articles about COVID-19, and finally give the most appropriate answer to the questions asked in order to gain insight information automatically. The model is applied to the COVID-19 open research dataset challenge (CORD-19) that’s has caught the attention of many researchers and it contains over 400,000 scholarly articles. The result of the proposed model has shown a good achievement, as it is explained in the result section. It was found that NLP is a good choice for tackling this global pandemic for information extraction and it contributes a new insight in support of the ongoing fight against this infectious disease. research dataset challenge (CORD-19) that has over 400,000 scholarly articles about COVID-19, SARS, CoV-2, and related coronavirus. It is a free dataset for researchers to apply to the field of Natural Language Processing and Artificial Intelligence techniques to find out new information that will make it easier to take part in the efforts against coronavirus. It is crucial to have a system that can enable easier extraction of the information needed from multiple articles using Natural Language Processing [3]. It will play an important role in facilitating the search process related to knowledge discovery as well as search engines. BERT, which is one of the models used in the retrieve automatic answer from documents, will be the one selected for this work. Finally, the required answers will be retrieved from a wide range of documents. This, as mentioned earlier, is important in contributing to the fight against COVID-19, as it will make it easier for researchers to find the information needed, and not waste time reading each article

Impacts of Illegal, Unreported and Unregulated (IUU) Fishing on Developing Countries: The Case of Somalia

Somalia, having the longest coastline in Africa is badly affected by IUU fishing. This research analyses the impacts of IUU fishing to Somalia, examines the root causes of the problem, and its effect on the nation and its people. This research also highlights the efforts by the Somalian government and regional administrations to combat IUU fishing

A Real-Time Flood Detection System Based on Machine Learning Algorithms with Emphasis on Deep Learning

A flood is expressed as water overflowing onto the ground, that usually is dry, or an increase of water that has a significant impact on human life, and it is also declared as one of the most usual natural phenomena, causing severe financial damage to goods and properties, as well as affecting human lives. However, preventing such floods would be useful to the inhabitants in order to get sufficient time to evacuate in the areas that might be susceptible to floods before they happen. Regarding the issue of floods, numerous scholars proposed different solutions, for instance, developing prediction models and building a proper infrastructure. Nevertheless, from an economical perspective, these proposed solutions are inefficient for people in countries like Somalia, for instance. Hence, the main objective of the present research paper is to propose a novel and robust model, which is a real-time flood detection system based on Machine-Learning-algorithms and Deep Learning; Random Forest, Naive Bayes J48, and Convolutional Neural Networks that can detect water level and measure floods with possible humanitarian consequences before they occur. The experimental results of this proposed method will be the solution to forth mentioned problems and conduct research on how it can be easily simulating a novel way that detects water levels using a hybrid model based on Arduino with GSM modems. Based on the analysis, the Random-Forest algorithm outperformed other machine learning models regarding the accuracy compared to the alternative classification methods with 98.7% of accuracy. In contrast, 88.4% and 84.2% were achieved using Naive Bayes and J48, respectively. On the other hand, using a Deep Learning approach achieved 87% of accuracy, showing overall good results on precision and recall. The proposed method has contributed to the field of study by introducing a new way of preventing floods in the field of Artificial Intelligence, data mining, and Deep Learning

Antenatal care utilization and its associated factors in Somalia: a cross-sectional study

Abstract Background WHO recommends attending minimum four ANC consultations during pregnancy to ensure early detection of complications. The objective of this study was to quantify ANC attendance and factors associated with it. Methods Participants were randomly selected using the WHO Cluster survey methodology in Southern and Central Somalia. A paper-print questionnaire was used to collect all data. Outcomes of interest were: access to at least one ANC consultation, completion of at least four ANC consultations, initiation of breastfeeding and place of delivery, while exposures included factors related to the latest pregnancy and demographic characteristics. Associations were assessed through logistic regression. Results Seven hundred ninety-two women answered the questionnaire; 85% attended at least one and 23% at least four ANC consultations, 95% started breastfeeding and 51% had an institutional delivery. Encouragement to attend ANC increased the odds of attending at least one consultation (aOR = 8.22, 95%CI 4.36–15.49), while negative attitude of husband or family decreased the odds (aOR = 0.33, 95%CI 0.16–0.69). Knowing there is a midwife increased the odds of at least four visits (aOR = 1.87, 95%CI 1.03–3.41). Attending at least four consultations increased the odds of delivering in a health structure (aOR = 1.50, 95%CI 1.01–2.24), and attending at least one consultation was associated with higher odds of initiating breastfeeding (aOR = 2.69, 95%CI 1.07–6.74). Conclusions Family has a strong influence in women’s ANC attendance, which increases the likelihood of institutional delivery and initiating breastfeeding. Women and families need to have access to information about benefits and availability of services; potential solutions can include health education and outreach interventions

Prevalence and Species Identification of Ixodid Ticks of Small Ruminants in Benadir Region, Somalia

Ixodid ticks are one of the major health constraints on small ruminant productivity and contribute to significant economic losses in Somalia. An across-sectional study was conducted from November 2019 through December 2020 to identify hard tick species and determine the prevalence of tick infestation in small ruminants in the Benadir region, Somalia. Ticks were identified at the genera and species level by using morphological identification keys under a stereomicroscope. During the study period, a total of 384 small ruminants were examined for the presence of ticks through purposive sampling. All visible individual adult ticks were collected from the bodies of 230 goats and 154 sheep. A total of 651 Ixodid adult ticks were collected, of which 393 were male and 258 were female. The overall prevalence of tick infestation in the study area was 66.15% (254/384). The prevalence of tick infestation in goats and sheep was found to be 76.1% (175/230) and 51.3% (79/154), respectively. In the present study, nine species of hard ticks, which were grouped into three genera, were identified. The most abundant species found in this study were Rhipichephalus pulchellus (64.97%), Rhipichephalus everstieversti (8.45%), Rhipichephalus pravus (5.53%), Rhipichephalus lunulatus (5.38%), Amblyomma lepidum (5.22%), Amblyomma gemma (3.38%), and Hyalomma truncatum (2.62%) according to predominance. Rhipichephalus bursa (2.46%) and Rhipichephalus turanicus (1.99%) were the minor species observed in both species in the study area. The difference in the prevalence of tick infestation was found to be a statistically significant variation (p<0.05) between species groups but not sex groups. In all cases, male ticks dominated female ticks. In conclusion, the findings of this study suggest that ticks were the most prevalent ectoparasites of small ruminants in the study areas. Therefore, the increasing threat of ticks and tick-borne pathogens of small ruminants warrants the urgent strategic application of acaricides and the creation of awareness among livestock owners to prevent and control tick infestations of sheep and goats in the study area