International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 1 Banana KBS Diagnosis and Treatment Hamza Rafiq Almadhoun Department of Information Technology, Faculty of Engineering and Information Technology, Al-Azhar University, Gaza, Palestine Abstract: This research involved the design of an initial expert system which helps farmers and specialists diagnose and provide appropriate advice on banana diseases. The management of knowledge used in the expert system was also discussed. One of the key elements of this research was to find the appropriate language to diagnose the disease and the current situation in the knowledge base. Expert systems enable effective consultation. Production rules were used to capture knowledge. The expert system was developed using CLIPS with the Delphi 10.2 as user interface. The expert system produced good results in analyzing cases of tested banana disease and enabling the system to determine the correct diagnosis in all cases. Keywords: Knowledge Based System; Banana; Diagnosis; Treatment. 1. INTRODUCTION Bananas are one of the most consumed fruits in the world for good reason. Taking them can help lower blood pressure and reduce the risk of cancer and asthma. Figure1: The banana Today, bananas are grown in at least 107 countries and are ranked fourth among the world's food crops in monetary value. Bananas are rich in potassium and fiber. They may help prevent asthma, cancer, high blood pressure, diabetes, cardiovascular disease, and digestive problems. Grown commercially as a food source, bananas also feature prominently in warm region gardens and conservatories, making striking additions to the landscape. When planted in areas with plenty of sun, bananas are not all that hard to grow, but problems with banana plants are bound to crop up nonetheless. What kinds of banana plant pests and diseases are there? Keep reading to find out how to solve problems with banana plants. Internationalists in agriculture do not treat banana diseases in many places. In fact, the presence of specialists and specialized centers for the treatment of banana diseases is rare in most parts of the world. Diagnosis of banana diseases is very complex. So they need specialists with extensive experience in banana diseases. For all the above reasons, We have developed this expert system to help specialists and farmers diagnose many of the banana diseases, in order to prescribe appropriate treatment. An expert system is an artificial intelligence computer application; which contains a knowledge base and a conclusion engine; the components and basic details are represented in Figure 2. A few of the advantages of expert systems are as follows:  Unlimited work hour: Human experts could not work continuously without a break, but expert systems could work at 24 hours a day since the day they were constructed;  Low cost of operation: It took a lot of time and money to train or hire a competent engineer, despite of the initial cost of the expert system, the daily cost is much less than using a human engineer.  Knowledge distribution: Expertise and knowledge are scarce resource. In today's knowledge-concentrated working environment, training a new staff requires lots of practice. When valuable employees leave the company, it is unlikely that the knowledge of him will be maintained. Expert system, on the other hand, could easily copy and restore the expertise knowledge.  Consistency: Different experts may make different decisions on a same issue according to their understanding of the current situation. Expert systems give consistent output.  Capability of computing: Because of the preset knowledge base and logical inference program, the expert system would do much better than its human counterpart in some time-consuming, complicated computing problem. International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 2 Figure 2: The figure presents the Main Components of an Expert System [17]. The proposed expert system for the diagnosis of banana diseases has been applied using Clips language with Delphi 10.2 as the user interface. It is a system of forward-thinking thinkers who can draw conclusions about the realities of the world using rules and things and take appropriate action as a result. Clips perform any expert system through the interfaces. It is easy for a knowledge engineer to build a system of experts and end users when they use the system. 2. MATERIALS AND METHODS The proposed experts system diagnoses 9 banana diseases by presenting symptoms of all problems to the user to select from. The proposed expert system asks the user to choose from the symptoms list of all problems. At the end of the dialogue session, the proposed expert system provides the diagnosis and recommendations for the user. Figure 12-17 shows the main user interface of the system. 3. LITERATURE REVIEW There are many expert systems designed to diagnose agricultural diseases such as potatoes, tomatoes and other diseases. However, there is no expert system for diagnosing banana diseases available for free. A few expert systems were developed to help farmers and specialists diagnose plant diseases using CLIPS [18, 19, 20]. The current expert system specializes in the diagnosis of banana diseases: Banana wilt; Mycosphaerella leaf spot, Yellow sigatoka, Black sigatoka; Anthracnose; Moko disease/bacterial wilt; Tip over or bacterial soft rot; Bunchy top/curly top; Banana bract mosaic virus (BBMV); Banana streak disease (BSV) and Infectious chlorosis (CMV). 1. KNOWLEDGE REPRESENTATION The main sources of knowledge for this expert system are Vikaspedia and a specialized site for agricultural diseases. The captured knowledge was converted to the structure of the Clips database (rules and object rules). The expert system currently contains bases covering 9 banana diseases: 1. Banana Wilt Disease symptoms:  Yellowing of the lower most leaves starting from margin to midrib of the leaves.  Yellowing extends upwards and finally heart leaf alone remains green for some time and it is also affected.  The leaves break near the base and hang down around pseudostem.  Longitudinal splitting of pseudostem. Discoloration of vascular vessels as red or brown streaks. Survival and spread:  The pathogen spreads through infected rhizomes. Favorable conditions:  Continuous cultivation in the infested field or monocroping results in buildup of inoculum. International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 3 Figure 3: shows the disease of banana wilt. 2. Mycosphaerella leaf spot, yellow sigatoka, black sigatoka Disease symptoms:  Early symptoms appear on the third or fourth leaf from the top, i.e., on young leaves.  Small spindle shaped spots on foliage with greyish center and yellowish halo running parallel to veins.  If the fruit is nearing maturity at the time of heavy infection, the flesh ripens but evenly and individual bananas appear undersized and their flesh develops a buff pinkish color, and store poorly. Survival and spread:  The conidia of the fungus are carried by wind ,rain water and old dried infected leaves and they help to spread the disease Figure 4: shows the disease of Mycosphaerella leaf spot, yellow sigatoka, black sigatoka 3. Anthracnose Disease symptoms:  At the initial stage, small, circular, black spots develop on the affected fruits. Then these spots enlarge in size, turn to brown color.  The skin of the fruit turns black and shrivels and becomes covered with characteristic pink acervuli. Finally the whole finger is affected. Later the disease spreads and affects the whole bunch.  The disease results in premature ripening and shriveling of the fruits which are covered with pink spore masses.  Occurrence if black lesions on the pedicel causes withering of the pedicel and dropping of the fingers from the hands.  Sometimes the main stalk of the bunch may become diseased. Infected fruits become black and rotten. Survival and spread:  The spread of the disease is by air-borne conidia and numerous insects which frequently visit banana flowers also spread the disease. Favorable conditions  The disease is favored by high atmospheric temperature and humidity, wounds and bruises caused in the fruit and susceptibility of the variety International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 4 Figure 5: shows the disease of Anthracnose. 4. Moko disease/bacterial wilt Disease symptoms:  Leaves become yellow and progress upwards. The petiole breaks and leaves hang.  When it is cut open discoloration in vascular region with pale yellow to dark brown color.  The discoloration is in the central portion of the corm.  Internal rot of fruits with dark brown discoloration.  When the pseudostem is cut transversely bacterial ooze can be seen. Survival and spread  The bacterium survives in infected plant material, vegetative propagative organs, wild host plants, and soil. Favorable conditions  High temperatures and high soil moisture generally favors disease. Figure 6: shows the disease of bacterial wilt 5. Tip over or Bacterial soft rot Disease symptoms:  This disease is more pronounced on young suckers leading to rotting and emitting of foul odor  Roting of collar region is a commonest symptom followed by epinasty of leaves, which dry out suddenly  If affected plants are pulled out it comes out from the collar region leaving the corm with their roots in the soil  In early stage of infection dark brown or yellow water soaked areas are more in the cortex area When affected plants are cut open at collar region yellowish to reddish ooze is seen. Survival and spread:  Bacteria survive in crop debris and infect by water splash through damaged tissues.  Worse in hot wet weather. The bacteria spread in contaminated water. Favorable conditions:  Higher temperatures and high humidity are ideal growing conditions for the bacteria Figure 7: shows the disease of Bacterial soft rot 6. Bunchy top/curly top International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 5 Disease symptoms:  Prominent dark green streaks on the petioles and midrib along the leaf veins.  Marginal chlorosis and curling of leaves  Petioles fail to elongate  Leaves are reduced in size, chlorotic, stand upright and become brittle and are crowded at the top (Bunchy top) and shoe dark green streaks with 'J hook' shape near the midrib.  Flowers display mottled and streaked discoloration  Plants show marked stunting Survival and spread:  Vector: banana aphid, Pentalonia nigronervosa  The disease can be spread by infected plant debris, plant wounds and injuries. Favorable conditions:  Hot and damp weather with plenty of rainfall trigger the disease to occur. Figure 8: shows the disease of Bunchy top/curly top 7. Banana bract mosaic virus (BBMV) Disease symptoms:  The disease is characterized by the presence of spindle shaped pinkish to reddish streaks on pseudostem, midrib and peduncle  Typical mosaic and spindle shaped mild mosaic streaks on bracts, peduncle and fingers also observed.  Suckers exhibit unusual reddish brown streaks at emergence and separation of leaf sheath from central axis  Clustering of leaves at crown with a travelers palm appearance, elongated peduncle and half-filled hands are its characteristic symptom. Survival and spread:  The disease is caused by a virus belonging to pot virus group. The virions are flexuous filamentous  The virus is transmitted through aphid vectors such as Aphis gosypii, Pentolonia nigronervosa and Rhopalosiphum maids. In field the disease spread mainly through suckers Figure 9: shows the disease of Banana bract mosaic virus 8. Banana streak disease (BSV) Disease symptoms:  A prominent symptom exhibited by BSV is yellow streaking of the leaves, which becomes progressively necrotic producing a black streaked appearance in older leaves. Survival and spread:  The virus is transmitted mostly through infected planting materials, though mealy bugs (Planococcus citric) and more probably Saccharicoccus sacchari are also believed to transmit it. Shoot tip culture does not eliminate it from vegetative propagated materials. International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 6 Figure 10: shows the disease of Banana streak disease (BSV) 9. Infectious chlorosis (CMV) Disease symptoms:  The disease manifests itself in all stages of crop growth.  Due to repeated use of suckers from infected plants the disease spreads and resulting in the gradual decrease in yield and quality.  The disease is known to occur in all banana-growing states.  Light yellow streaks run parallel to leaf veins giving the leaf a striped appearance.  The streaks run usually from mid rib to edge of the blade. Survival and spread  Virus is disseminated by suckers and Aphis gossipy. Figure 11: shows the disease of Infectious chlorosis (CMV): 4. LIMITATIONS The current system of experts specializes in diagnosing only the following 9 diseases: Banana wilt; Mycosphaerella leaf spot, Yellow sigatoka, Black sigatoka; Anthracnose; Moko disease/bacterial wilt; Tip over or bacterial soft rot; Bunchy top/curly top; Banana bract mosaic virus (BBMV); Banana streak disease (BSV) and Infectious chlorosis (CMV). 5. CONCLUSION In this paper, a proposed expert system was introduced to help farmers, specialist, and students diagnose banana disease. Farmers, specialist and students can get a faster and more accurate diagnosis than the traditional method. This expert system does not require extensive training to use; it is easy to use and has an easy-to-use interface. The proposed expert system was developed using CLIPS and Delphi 10.2 language as the user interface. 6. FUTURE WORK This expert system is a basis for the future. It is planned to add more banana diseases and make it easier for users from anywhere and at any time. 7. EXPERT SYSTEM IMAGES International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 7 Figure 12: The main screen of the expert system. Figure 13: Add Info screen for the main interface. International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 8 Figure 14: Main interface adjustment screen. Figure 15: Screen Modifying User Interface. Figure 15: Screen Add Disease Interface. International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 9 Figure 16: Screen selection sickness Figure 17: Screen shows the diagnosis of the banana disease REFERENCES 1. Abu Naser, S. S. (1993). A methodology for expert systems testing and debugging, North Dakota State University, USA. 2. Abu Naser, S. S. (1999). "Big O Notation for Measuring Expert Systems complexity." Islamic University Journal Gaza 7(1): 57-70. 3. Azaab, S., et al. (2000). "A proposed expert system for selecting exploratory factor analysis procedures." Journal of the College of Education 4(2): 9-26. 4. Kashkash, K., et al. (2005). "Expert system methodologies and applications-a decade review from 1995 to 2004." Journal of Artificial Intelligence 1(2): 9-26. 5. Abu Naser, S. S. and A. Z. A. Ola (2008). "AN EXPERT SYSTEM FOR DIAGNOSING EYE DISEASES USING CLIPS." Journal of Theoretical & Applied Information Technology 4(10). 6. Abu Naser, S. S., et al. (2008). "A Proposed Expert System For Guiding Freshman Students In Selecting A Major In Al-Azhar University, Gaza." Journal of Theoretical & Applied Information Technology 4(9). 7. Abu-Naser, S. S. and A. N. Akkila (2008). "A Proposed Expert System for Skin Diseases Diagnosis." Journal of Applied Sciences Research 4(12): 16821693. 8. Abu Naser, S., et al. (2010). "Knowledge management in ESMDA: expert system for medical diagnostic assistance." Artificial Intelligence and Machine Learning Journal 10(1): 31-40. 9. Abu-Naser, S. S., et al. (2010). "An expert system for endocrine diagnosis and treatments using JESS." Journal of Artificial Intelligence; Scialert 3(4): 239-251. 10. Abu-Naser, S. S., et al. (2010). "Developing an expert system for plant disease diagnosis." Journal of Artificial Intelligence ; Scialert 3(4): 269-276. 11. Abu Naser, S. S. (2015). "Sl5 Object: Simpler Level 5 Object Expert System Language." International Journal of Soft Computing, Mathematics and Control (IJSCMC) 4(4): 25-37. 12. Naser, S. S. A. and M. M. Hilles (2016). "An expert system for shoulder problems using CLIPS." World Wide Journal of Multidisciplinary Research and Development 2(5): 1-8. 13. Abu Naser, S. S. and A. E. A. El-Najjar (2016). "An expert system for nausea and vomiting problems in infants and children." International Journal of Medicine Research 1(2): 114-117. 14. Abu Naser, S. S. and A. O. Mahdi (2016). "A proposed Expert System for Foot Diseases Diagnosis." American Journal of Innovative Research and Applied Sciences 2(4): 155-168. 15. Abu Naser, S. S. and B. G. Bastami (2016). "A proposed rule based system for breasts cancer diagnosis." World Wide Journal of Multidisciplinary Research and Development 2(5): 27-33. International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 10 16. Abu Naser, S. S. and I. S. Zaqout (2016). "Knowledge-based systems that determine the appropriate students major: In the faculty of engineering and information technology." World Wide Journal of Multidisciplinary Research and Development 2(10): 26-34. 17. Abu Naser, S. S. and M. A. Hamed (2016). "An Expert System for Mouth Problems in Infants and Children." Journal of Multidisciplinary Engineering Science Studies (JMESS) 2(4): 468-476. 18. Abu Naser, S. S. and M. H. Al-Bayed (2016). "Detecting Health Problems Related to Addiction of Video Game Playing Using an Expert System." World Wide Journal of Multidisciplinary Research and Development 2(9): 7-12. 19. Abu Naser, S. S. and M. I. Alhabbash (2016). "Male Infertility Expert system Diagnoses and Treatment." American Journal of Innovative Research and Applied Sciences 2(4). 20. Abu Naser, S. S. and M. M. Al-Hanjori (2016). "An expert system for men genital problems diagnosis and treatment." International Journal of Medicine Research 1(2): 83-86. 21. Abu Naser, S. S. and M. W. Alawar (2016). "An expert system for feeding problems in infants and children." International Journal of Medicine Research 1(2): 79-82. 22. Abu Naser, S. S. and M. Z. Shaath (2016). "Expert system urination problems diagnosis." World Wide Journal of Multidisciplinary Research and Development 2(5): 9-19. 23. Abu Naser, S. S. and R. M. AlDahdooh (2016). "Lower Back Pain Expert System Diagnosis and Treatment." Journal of Multidisciplinary Engineering Science Studies (JMESS) 2(4): 441-446. 24. Abu Naser, S. S. and S. H. ALmursheidi (2016). "A Knowledge Based System for Neck Pain Diagnosis." World Wide Journal of Multidisciplinary Research and Development (WWJMRD) 2(4): 12-18. 25. Abu Naser, S. S., et al. (2016). "Rule Based System for Diagnosing Wireless Connection Problems Using SL5 Object." International Journal of Information Technology and Electrical Engineering 5(6): 26-33. 26. Akkila, A. N. and S. S. Abu Naser (2016). "Proposed Expert System for Calculating Inheritance in Islam." World Wide Journal of Multidisciplinary Research and Development 2(9): 38-48. 27. Naser, S. S. A. and H. A. A. Hasanein (2016). "Ear Diseases Diagnosis Expert System Using SL5 Object." World Wide Journal of Multidisciplinary Research and Development 2(4): 41-47. 28. Naser, S. S. A. and M. A. Al-Nakhal (2016). "A Ruled Based System for Ear Problem Diagnosis and Treatment." World Wide Journal of Multidisciplinary Research and Development 2(4): 25-31. 29. Abu Ghali, M. J., et al. (2017). "Expert System for Problems of Teeth and Gums." International Journal of Engineering and Information Systems (IJEAIS) 1(4): 198-206. 30. AbuEl-Reesh, J. Y. and S. S. Abu Naser (2017). "A Knowledge Based System for Diagnosing Shortness of Breath in Infants and Children." International Journal of Engineering and Information Systems (IJEAIS) 1(4): 102-115. 31. Al Rekhawi, H. A., et al. (2017). "Rickets Expert System Diagnoses and Treatment." International Journal of Engineering and Information Systems (IJEAIS) 1(4): 149-159. 32. Bakeer, H. and S. S. Abu Naser (2017). "Photo Copier Maintenance Expert System V. 01 Using SL5 Object Language." International Journal of Engineering and Information Systems (IJEAIS) 1(4): 116-124. 33. El Agha, M., et al. (2017). "Polymyalgia Rheumatic Expert System." International Journal of Engineering and Information Systems (IJEAIS) 1(4): 125137. 34. Khella, R. and S. S. Abu Naser (2017). "Rule Based System for Chest Pain in Infants and Children." International Journal of Engineering and Information Systems 1(4): 138-148. 35. Mrouf, A., et al. (2017). "Knowledge Based System for Long-term Abdominal Pain (Stomach Pain) Diagnosis and Treatment." International Journal of Engineering and Information Systems (IJEAIS) 1(4): 71-88. 36. Nabahin, A., et al. (2017). "Expert System for Hair Loss Diagnosis and Treatment." International Journal of Engineering and Information Systems (IJEAIS) 1(4): 160-169. 37. Almurshidi, S. H. and S. S. Abu-Naser (2018). EXPERT SYSTEM FOR DIAGNOSING BREAST CANCER, Al-Azhar University, Gaza, Palestine. 38. Alajrami, M. A. and S. S. Abu-Naser (2018). "Onion Rule Based System for Disorders Diagnosis and Treatment." International Journal of Academic Pedagogical Research (IJAPR) 2(8): 1-9. 39. Almadhoun, H. R. and S. S. Abu Naser (2018). "Banana Knowledge Based System Diagnosis and Treatment." International Journal of Academic Pedagogical Research (IJAPR) 2(7): 1-11. 40. Almurshidi, S. H. and S. S. Abu-Naser (2018). "Breast Cancer Knowledge Based System." International Journal of Academic Health and Medical Research (IJAHMR) 2(12): 7-22. 41. AlZamily, J. Y. and S. S. Abu-Naser (2018). "A Cognitive System for Diagnosing Musa Acuminata Disorders." International Journal of Academic Information Systems Research (IJAISR) 2(8): 1-8. 42. Barhoom, A. M. and S. S. Abu-Naser (2018). "Black Pepper Expert System." International Journal of Academic Information Systems Research (IJAISR) 2(8): 9-16. 43. Dahouk, A. W. and S. S. Abu-Naser (2018). "A Proposed Knowledge Based System for Desktop PC Troubleshooting." International Journal of Academic Pedagogical Research (IJAPR) 2(6): 1-8. 44. Elqassas, R. and S. S. Abu-Naser (2018). "Expert System for the Diagnosis of Mango Diseases." International Journal of Academic Engineering Research (IJAER) 2(8): 10-18. 45. Kashf, D. W. A., et al. (2018). "Predicting DNA Lung Cancer using Artificial Neural Network." International Journal of Academic Pedagogical Research (IJAPR) 2(10): 6-13. 46. Metwally, N. F., et al. (2018). "Diagnosis of Hepatitis Virus Using Artificial Neural Network." International Journal of Academic Pedagogical Research (IJAPR) 2(11): 1-7. 47. Musleh, M. M. and S. S. Abu-Naser (2018). "Rule Based System for Diagnosing and Treating Potatoes Problems." International Journal of Academic Engineering Research (IJAER) 2(8): 1-9. 48. Nassr, M. S. and S. S. Abu Naser (2018). "Knowledge Based System for Diagnosing Pineapple Diseases." International Journal of Academic Pedagogical Research (IJAPR) 2(7): 12-19. 49. Abu-Saqer, M. M. and S. S. Abu-Naser (2019). "Developing an Expert System for Papaya Plant Disease Diagnosis." International Journal of Academic Engineering Research (IJAER) 3(4): 14-21. 50. Abu-Saqer, M. M. and S. S. Abu-Naser (2019). "Developing an Expert System for Uveitis Disease Diagnosis." International Journal of Academic Information Systems Research (IJAISR) 3(5): 18-25. International Journal of Academic Pedagogical Research (IJAPR) ISSN: 2000-004X Vol. 2 Issue 7, July – 2018, Pages: 1-11 www.ijeais.org/ijapr 11 51. Abu-Saqer, M. M. and S. S. Abu-Naser (2019). "Knowledge Based System for Uveitis Disease Diagnosis." International Journal of Academic Information Systems Research (IJAISR) 3(5): 18-25. 52. Alajrami, M. A. and S. S. Abu-Naser (2019). "Grapes Expert System Diagnosis and Treatment." International Journal of Academic Engineering Research (IJAER) 3(5): 38-46. 53. Aldaour, A. F. and S. S. Abu-Naser (2019). "An Expert System for Diagnosing Tobacco Diseases Using CLIPS." International Journal of Academic Engineering Research (IJAER) 3(3): 12-18. 54. Aldaour, A. F. and S. S. Abu-Naser (2019). "Anemia Expert System Diagnosis Using Sl5 Object." International Journal of Academic Information Systems Research (IJAISR) 3(5): 9-17. 55. Al-Qumboz, M. N. A. and S. S. Abu-Naser (2019). "Spinach Expert System: Diseases and Symptoms." International Journal of Academic Information Systems Research (IJAISR) 3(3): 16-22. 56. Al-Qumboz, M. N. A., et al. (2019). "Kidney Expert System Diseases and Symptoms." International Journal of Academic Engineering Research (IJAER) 3(5): 1-10. 57. Alshawwa, I. A., et al. (2019). "An Expert System for Coconut Diseases Diagnosis." International Journal of Academic Engineering Research (IJAER) 3(4): 8-13. 58. Alshawwa, I. A., et al. (2019). "An Expert System for Depression Diagnosis." International Journal of Academic Health and Medical Research (IJAHMR) 3(4): 20-27. 59. Al-Shawwa, M. and S. S. Abu-Naser (2019). "Knowledge Based System for Apple Problems Using CLIPS." International Journal of Academic Engineering Research (IJAER) 3(3): 1-11. 60. Al-Shawwa, M. and S. S. Abu-Naser (2019). "Predicting Birth Weight Using Artificial Neural Network." International Journal of Academic Health and Medical Research (IJAHMR) 3(1): 9-14. 61. Al-Shawwa, M. and S. S. Abu-Naser (2019). "Predicting Effect of Oxygen Consumption of Thylakoid Membranes (Chloroplasts) from Spinach after Inhibition Using Artificial Neural Network." International Journal of Academic Engineering Research (IJAER) 3(2): 15-20. 62. Al-Shawwa, M. O. and S. S. Abu-Naser (2019). "A Proposed Expert System for Diagnosing Skin Cancer Using SL5 Object." International Journal of Academic Information Systems Research (IJAISR) 3(4): 1-9. 63. Dalffa, M. A., et al. (2019). "Tic-Tac-Toe Learning Using Artificial Neural Networks." International Journal of Engineering and Information Systems (IJEAIS) 3(2): 9-19. 64. Dheir, I. and S. S. Abu-Naser (2019). "Knowledge Based System for Diagnosing Guava Problems." International Journal of Academic Information Systems Research (IJAISR) 3(3): 9-15. 65. Dheir, I. M., et al. (2019). "Knowledge Based System for Diabetes Diagnosis Using SL5 Object." International Journal of Academic Pedagogical Research (IJAPR) 3(4): 1-10. 66. El Kahlout, M. I. and S. S. Abu-Naser (2019). "An Expert System for Citrus Diseases Diagnosis." International Journal of Academic Engineering Research (IJAER) 3(4): 1-7. 67. El Kahlout, M. I., et al. (2019). "Silicosis Expert System Diagnosis and Treatment." International Journal of Academic Information Systems Research (IJAISR) 3(5): 1-8. 68. El-Khatib, M. J., et al. (2019). "Glass Classification Using Artificial Neural Network." International Journal of Academic Pedagogical Research (IJAPR) 3(2): 25-31. 69. El-Mashharawi, H. Q. and S. S. Abu-Naser (2019). "An Expert System for Sesame Diseases Diagnosis Using CLIPS." International Journal of Academic Engineering Research (IJAER) 3(4): 22-29. 70. El-Mashharawi, H. Q., et al. (2019). "An Expert System for Arthritis Diseases Diagnosis Using SL5 Object." International Journal of Academic Health and Medical Research (IJAHMR) 3(4): 28-35. 71. Elsharif, A. A. and S. S. Abu-Naser (2019). "An Expert System for Diagnosing Sugarcane Diseases." International Journal of Academic Engineering Research (IJAER) 3(3): 19-27. 72. Elsharif, A. A., et al. (2019). "Hepatitis Expert System Diagnosis Using Sl5 Object." International Journal of Academic Information Systems Research (IJAISR) 3(4): 10-18. 73. Mansour, A. I. and S. S. Abu-Naser (2019). "Expert System for the Diagnosis of Wheat Diseases." International Journal of Academic Information Systems Research (IJAISR) 3(4): 19-26. 74. Mansour, A. I. and S. S. Abu-Naser (2019). "Knowledge Based System for the Diagnosis of Dengue Disease." International Journal of Academic Health and Medical Research (IJAHMR) 3(4): 12-19. 75. Masri, N., et al. (2019). "Survey of Rule-Based Systems." International Journal of Academic Information Systems Research (IJAISR) 3(7): 1-23. 76. Mettleq, A. S. A. and S. S. Abu-Naser (2019). "A Rule Based System for the Diagnosis of Coffee Diseases." International Journal of Academic Information Systems Research (IJAISR) 3(3): 1-8. 77. Mettleq, A. S. A., et al. (2019). "Expert System for the Diagnosis of Seventh Nerve Inflammation (Bell's palsy) Disease." International Journal of Academic Information Systems Research (IJAISR) 3(4): 27-35. 78. Sadek, R. M., et al. (2019). "Parkinson's Disease Prediction Using Artificial Neural Network." International Journal of Academic Health and Medical Research (IJAHMR) 3(1): 1-8. 79. Salman, F. and S. S. Abu-Naser (2019). "Rule based System for Safflower Disease Diagnosis and Treatment." International Journal of Academic Engineering Research (IJAER) 3(8): 1-10. 80. Salman, F. M. and S. S. Abu-Naser (2019). "Expert System for Castor Diseases and Diagnosis." International Journal of Engineering and Information Systems (IJEAIS) 3(3): 1-10. 81. Salman, F. M. and S. S. Abu-Naser (2019). "Thyroid Knowledge Based System." International Journal of Academic Engineering Research (IJAER) 3(5): 11-20. 82. Abu-Nasser, Bassem. "Medical Expert Systems Survey." International Journal of Engineering and Information Systems (IJEAIS) 1, no. 7 (2017): 218224. 83. Abu-Nasser, Bassem S., and Samy S. Abu-Naser. "Cognitive System for Helping Farmers in Diagnosing Watermelon Diseases." International Journal of Academic Information Systems Research (IJAISR) 2, no. 7 (2018): 1-7. 84. Abu-Nasser, Bassem S., and Samy S. Abu Naser. "Rule-Based System for Watermelon Diseases and Treatment." International Journal of Academic Information Systems Research (IJAISR) 2, no. 7 (2018): 1-7.