Authors:Salaheldin Edam, Doaa Abubakr, Roaa Rahma, Roaa Yagoub Pages: 1 - 10 Abstract: Localization in wireless sensor networks is essential not only for determining the location but also for routing, managing density, tracking, and a wide range of other communication network functions. There are two main categories of localization algorithms in wireless sensor networks: range-based algorithms and range-free techniques. Localization based on range-free algorithms has benefits in terms of requiring less hardware and energy, making it cost-efficient. This paper examines the impact of beacon nodes on range-free localization algorithms. The findings indicate that ADLA has intermediate localization errors and the best detecting nodes. It also addresses the effect of the number of locators on the algorithm’s efficiency. The findings demonstrate that as the number of locators increased, the number of detected nodes in Centroid also increased. Compared to Centroid, ADLA has the second-best detecting nodes but with better average error. Moreover, it considers the impact of the number of static nodes on range-free localization algorithms, and ADLA achieved the best detection nodes. According to the evaluated results, this paper proposes a hybrid algorithm that combines the Centroid algorithm and Active Distributed Localization Algorithm (ADLA) algorithm. However, combining these two algorithms results in less localization error. PubDate: 2024-05-23 DOI: 10.4314/ijest.v16i2.1 Issue No:Vol. 16, No. 2 (2024)
Authors:Nyatwere D. Mganga, Robin E. Sanga Pages: 11 - 20 Abstract: Vegetable constitutes a healthy diet which is rich in vitamins, minerals and fibre. However, production of vegetable is currently hindered by several factors including pest infestation/pathogen infection. Pests and pathogens affect vegetable by interfering with growth and yield. The impacts may be manifested in holes on leaves or reduced numbers of leaves that subsequently affect the yield. To overcome problems associated with pests and/or pathogens synthetic pesticides are widely used. However, synthetic pesticides are blamed to be costful and environmentally unfriendly. As a result vegetable growers in many countries have decided to rely on local pesticides in attempt to improve growth and yield of crops. This study aims to evaluate the efficacy of a mixture of wood ash and soil, cow urine, pawpaw seeds, chilli fruits and neem leaves for growing Chinese cabbage which is widely consumed in Tanzania. Standard methods were used to prepare extracts of the aforementioned local materials and later on sprayed on growing Chinese cabbage. Normal water was used for control plots. The results of One Way ANOVA revealed significant difference in leaf damage and yield of Chinese cabbage (p < 0.05). The order of increasing effectiveness of the local materials in protecting leaves of Chinese cabbage was: mixture of wood ash and soil > cow urine > pawpaw seeds > chilli fruits > neem leaves > control. A similar trend was obtained for improvement of yield of Chinese cabbage. Intactness of leaves and improved yield of Chinese cabbage can be attained by spraying a mixture of wood ash and soil, and cow urine. Further studies are recommended on the efficacy of the studied local materials in other horticultural crops. Also isolation of active compounds in mixture of wood ash and soil, and cow urine for development of cheap and environmentally friendly pesticide is recommended. PubDate: 2024-05-23 DOI: 10.4314/ijest.v16i2.2 Issue No:Vol. 16, No. 2 (2024)
Authors:Washa Bugalama Washa Pages: 21 - 26 Abstract: Mushrooms are nutritious foods with medicinal value. Cultivation of mushrooms is hindered by poverty in Tanzania communities. A study to establish mushroom cultivation techniques at affordable cost was conducted at Kinyerezi Dare s Salaam Tanzania in 2022. Three replicate comprising greenhouse setup and substrate ratios comprising saw dust, banana leaves, grain chaff, lime and sugar were established and tested their production ability. Substrates were packaged in 100 bags of 2 kg each in their respective ratios 30:30:15:15:15, 25:25:10:10:10 and 20:20;5:5:5 where mushroom spores were inoculated and sparingly watered for 30 days to allow germination. Mushrooms were harvested twice a week for three months to record germination number and percentage. Data were analysed using SPSS version 16 for descriptive and inferential statistics. Obtained data were summarized into tables for interpretation and discussion. Woody greenhouse of palm frond created the most optimal conditions for mushroom growth which were 75% humidity, 250C and 7.5 pH. Substrate combination in a ratio of 20:20:5:5:5 with additional of extra 2 kg sugar produced highest germination percentage and number which were 17% and 172.8 respectively and indicated a significant difference between trials in germination percentage P=0.002248, df=2 but not significantly different in germination number P=0.25246, df=2. It was concluded that, edible mushroom can be grown at an affordable cost using woody greenhouse which influence optimal growth conditions, but also researchers on future should think on using constant substrate ratio while assessing the others to see if can alter germination number and percentage. It was recommended to the community to acquare the techniques so as to produce mushroom for health and economy. PubDate: 2024-05-23 DOI: 10.4314/ijest.v16i2.3 Issue No:Vol. 16, No. 2 (2024)
Authors:K.T. Tsapi, G.F. Kuiate, B.D. Soh Fotsing Pages: 27 - 39 Abstract: The democratization of industrial processes, fueled by the proliferation of fabrication laboratories (Fab Labs), is gradually paving the way for the accelerated development of the use of advanced manufacturing technologies in African countries. However, a comprehensive study that provides a holistic view of the contributions of the Fab Labs in Cameroon is lacking. Therefore, this paper presents a critical analysis of the state of Fab Labsdevelopment in Cameroon.A case study was used to analyze the occupational health and safety (OHS) risks at the laser cutting and milling operator workstations at XYZ Fabby using the Job Safety Analysis (JSA) to identify hazards and the AS/ NZS 4360:2004 standardto calculate the risk score.The results showed that the Fab Lab ecosystem in Cameroon consists of 10 active labs, with universities hosting 40% and private companies and social enterprises hosting 60%. Through their various activities, these Fab Labs collectively empower user communities and bridge the digital divide, enabling economic and industrial development through innovative projects and better access to cross-cutting science, technology and engineering practices. The results of the risk analysis showed that the risk level of each hazardous activity of the laser cutter operator workstation consisted of two levels, i.e., substantial with 75.0% and acceptable with 25.0%. Meanwhile, the risk level of the milling machine operator workstation consisted of three risk levels, i.e., acceptable with 69.2%, priority 3 with 7.7% and substantial with 23.1%. Recommendations were made to reduce or eliminate the effects of hazards associated with machine use, such as proper training and adherence to clear safety policies and procedures to be implemented.University-industry partnerships were recommended to strengthen and expand the number of Fab Labs in Cameroon, promote rapid prototyping, and foster innovation and entrepreneurship from universities. PubDate: 2024-05-23 DOI: 10.4314/ijest.v16i2.4 Issue No:Vol. 16, No. 2 (2024)
Authors:Hariharasudan Natarajan, Prakash M. Alagundi Pages: 40 - 47 Abstract: The present study introduces a coating approach for realization of antimicrobial textile surfaces that does not rely on nano-scale metal particles. Instead, bactericidal metal ions are used in place of elemental metal particles and are deposited in alginates that are adhered to the textile substrate through coating application. Antimicrobial finishing of polyester fabrics is challenging due to the limited permanence resulting from the hydrophobic nature of polyester fibers. A high-temperature (HT) derived process is now presented as a promising opportunity for introducing functions on polyester fabrics. For instance, an approach of antimicrobial finishing is presented; the applied antimicrobial agent consisted of a modified carbohydrate which cannot be bonded to the textile surface in a HT process. Therefore, different silane linker molecules were utilized, either comprising an alkyl or vinyl functional group. In terms of antimicrobial testing, the viability assay was carried out against the following pathogens, Escherichia coli and Staphylococcus aureus. Promising antibacterial results were witnessed and are likely to pave the way for future coating applications on textiles and other polymers substrates. PubDate: 2024-05-23 DOI: 10.4314/ijest.v16i2.5 Issue No:Vol. 16, No. 2 (2024)
Authors:S. Prithi, S. Sumathi Pages: 48 - 67 Abstract: Network Security plays an essential role in the modern world. Current network services mainly rely on processing of payload in packets. Deep Packet Inspection (DPI) is a key factor in examining the packet payload which uses the signatures to identify the packet that carries any viruses, worms, malicious traffic, unauthorized access and attacks. DPI uses regular expression matching as a core operator to examine the packet payload. Finite State Automata (FSA) are natural representations for regular expression. FSA is usually too large to be constructed or deployed and has a huge overhead. Finite State Automata frequently leads to state explosion problem which require more storage space, high bandwidth and more computational time. To overcome this problem, Intelligent Optimization Grouping Algorithms (IOGA) can be used to distribute the regular expressions into various groups and for each group the Deterministic Finite Automata (DFA) are built independently. Grouping the regular expression efficiently solves the state explosion problem by achieving large-scale best tradeoff among the memory utilization and computational time. This paper reviews the various Intelligent Optimization Grouping Algorithms like Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bacterial Foraging Optimization, Artificial Bee Colony Algorithm, Biogeography Based Optimization, Cuckoo Search, Firefly Algorithm, Bat Algorithm and Flower Plant Optimization. The discussions states that by effectively using these grouping algorithms along with finite state automata can reduce the number of states by solving the state explosion blow up problem, providing a balance between the memory consumption, number of groups and provide faster convergence. PubDate: 2024-05-23 DOI: 10.4314/ijest.v16i2.6 Issue No:Vol. 16, No. 2 (2024)
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