data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAKAAAAB4CAYAAAB1ovlvAAAAAXNSR0IArs4c6QAAFdtJREFUeF7tnQd01VWawL+XnhB6DR1ERKqiy1KUJigqiPTBOTjoUWQGBDky7LorM+pQZuSsKLOrDuPoDMg4UkYURVQWC0pTeu8hQCgRElpIecnb87vhe/seLe8FHvH/z73n5Lz2L7f88n33K/f+PT6fzye22B4opR7wWABLqeftbU0PGABzcnJk9+7dcvz4ccnPz49I10RC0FapUkXKly8vzZs3j0id7UUj3wMer9frW758udSpU+ea75aUlCgr/zBMEjP3XfO1rnqBqGi5feQrcq5aC/MPwz9Q27ZtI3tPe/WI9IBnzZo1vqSkJHPxI0eOSO3ateVy0oqBBtR9+/aZwQ4c8IMHD0q9evUkNjpKCv7YS+rXqyMSFSO+E6khV9qTXE3EEyW+M8cvOSeqXhspPLjRfB+V0lwKj2wTT9fRklr/QfPdoUOH5L777gv5XvbAn04PGACjo6NNjZYsWWLUcEFBgXg8HqlQoYLs379fHn/8cZk5c6Z069bNfG7QoIHMmzdP+vXrZ6D94Ycf5JVXXpEYj4jn7cHS5BcvG4i9q+eIJyFZJC5JxFco3k2fSGzbAVKQvkUALqpSivjOZYkkVRTJzRaJTRBPdKz4zmSIp1JtyV81W2La9pfoum3Eu+lj8ZSvLuLNE+/2peLpMlp21uph6p2bmyt33nmnxMbG/nR61tYkpB7wLF++3BcTE2MO/vTTT+XcuXPSqVMn+fDDDw1o/MZ3QFq1alU5cOCA1K9f3y8lT58+LSdPnpShQ4dKxeRyEvO3odKo80CRxAoSXauZ+LJPSuGJNCMNC9LWS8LP/0e8mxaLL/esFB7eInHdR0nBwU3iKVdZPEmVpPD4HvEklBdP+RqSu/B5iesxTjzVG4ucP2WgLdi7QvJXzhLpPEq2VO1i6n3q1Cnp2bOnREVFhdRoe9BPpwc86enpvu+//14qVapkagVwSK/NmzdL7969DXDAh1TU18LCQomLixOv1yu853skphR6pdrfh0pK8gUQ+M44eQI8PVf87sIx5nefUcdITQn6zDFFxxV0GSMbk9uZ9xkZGTJgwICfTq/amoTcA8YK3rJli6xevVrq1q1rYLqW0qBWVfHknbuWSxR/ridKMr2xcvjwYTl//rzce++9Rjrb4rwe8PsBkWSoU16dUuLj46VcuXJOqa6t52V6wDqiLRal2gMWwFLtfntzC6BloFR7wAJYqt1vb24BtAyUag9YAEu1++3NLYCWgVLtAQMgyQT8ZWVlXXNliIhoVKW4i/3444/G8V2jRg0Ty7Wl7PWA5/Dhwz4SDKpXr35dWu/z5suByd2lYcWi+PLVSvWBL0hG3aJ4bmpqqolo2FK2esCzYcMGH0F8JBcxYF5JRHj44Yfl6NGjJlGVLBMkVfv27WXDhg3SokUL+eijj2Tw4MEmE0XP4zU9dY/c8dUYSSA1JqDEtB0g3nULgr4j0WBXSk9z/okTJ6Rr165lq/dta8UkI6Snp5uumD17tmzcuFGaNWtmMmCQioTnAPD+++830BH6+vrrr+Wee+4xUHJcxYoVzXevv/66HNq3S9otH+cHkBSqqNotJLbjcMl5Z/glAG6u0tn/3e23324zWsoYlCYfkKwWChkwycnJZg6nSabM08iQ6dixo7z22msmETUlJUWys7MNfByPBCMuW7lyZTl2cL90WDE+SAJGN24vcT3HSc6sEeI7f8rfxUjAtcntzWckINk3tpStHvCkpqaadKzrNQf05pyTtkufktioYBV8uW7N6/GcbI4rWs+Buh8yZEjZ6n3b2qJFSbt27ZK1a9eabOjrUZCQiYmJV70UUjMtLc3kGd58883ywAMPXI9b22s4rAesH9BhA+a26loA3TaiDmuPBdBhA+a26loA3TaiDmuPBdBhA+a26loA3TaiDmuPBdBhA+a26loA3TaiDmuPBdBhA+a26gYBeObMGdm2bZtJPtANi25UgzUjhgXmt9566426rb1PKfdAEIDfffed2R3hcoVk1YsTTdmZgB2z2Btm+PDhQdDu3LlTbrnllrCbl5eXZxbHl+TcsG9mTyj1HggCcNOmTWbDR6TRSy+9ZCAg44UsF9KtbrrpJpMvyFZsALlu3Tp588035e233zbbthHTJbWrUaNGZhetZ599tkQNRBK3bt26ROfak5zVA0EAAhEFAKdMmWJSr7799ltp166dSdUCRHIASWAFEmB94oknZM6cOf50qs8++8zkE65Zs0aee+65EvUGEN91110lOtee5KweCAJwz549/sxoIOMvMNuZtHmkm+6UharUTGqOA07dW4ZzyTMMzLQOvNbVvgfAu+++21k9aWtboh4IApD0ewrwnNixShJOHSjRRcM9qcDnkcqdhvr3p2bTy86d/z9TOtzr2eOd0wNBAJIXSMEK3vObjvKvteNlR8P+crpRdynwxF7Yt0/377vyayiSLkp8Ujljg9Te/g+pWJApuRPWGzVOAcAuXYoWK9ni7h4IAnDHjh1+ANNe6ChRXUdLg3uGme8SEuJl9Ru/k8Jj+69rj3hq1Zce5z+VnF+vE9L/FUC2A7bF/T0QBOD27dtNi9n9dM+L3aTKqHlyNjvbbNVbkJcrR5/uIDUTi3Y/jW/cWnL3bQrqofiGLSQ3dav5zhMTK9GVa0pBVob48nOv2JNRvUbIiWObpfHovwYB2L17d/f3fim3EJeXur10vq9VQovpvJ41QcztdfN6nd8H2gB6ntkpl/G/sMqSfcavVoIAxAnNTQBw66QHpeXExcaSZTHSmaxMyXqhn9zyiwlSmH3a7JSbvekbc219rdJ/jGR+PFN8eTmS3KmvxFavJwVnMyU/fa9EJVeSc2uWmOMTW90lUuCVgtMnJb9FFzmUsVdajnrDbLXL/Vkfwqo7WyLbA2fPnjXejMApE3BhZAIdUyKWTaCZWH7Lb6yKZBUkhee0EDggaMFTFIAOKNWA5f2V/Mp+YAOflMRWvSoBt03uLS2e/0QmTZokY8eOlcT4ODn9Yn9p3OtnEl2xmvjyzhvJdnrZ++I9ecScV/mhX0rWkncMgBV6/FwSm94pMdXrSM6utRJbs4EcffVXRRUfMl5iKtWQrE/ekrzmnf0A6poUAOzRo2gHfFsi1wOBAHIXlXqAs2rVKvP8FVY7IiXZmB7fLmt98G4AIcDhJ+b42267zayQDJSggFjc82eCJCC+PgVw+5Q+cut/LDJ0IxHTDx6QnOfvl5q1U4xarfPbuZI+ZZgU5p6X6PKVpTAnW1LGvS5HXx0lnvhESWrZSbxZxyVn1zrxxMZJVFIFKTyTaTYd9ySWE/Hmi89XKL5uj0rawc1GAgYCyK73tkS2B5B+/AVCg+RbunSpCTQw9oAXqIJ5IgESEekHfECWkJAgNWvWNLAi8fQxH/zGc2euVoIAZFE6hQttn9pHmv37R0GVS07fJvm7117XXilo2EbSVrwvrUa/aVQvhVf74Jnr2s2XvZhKQFWbgPbNN98YKAEPKQdkfA9MrAXHQ8JzYdgcHglIcAIJiX+YTQyI47PEV+eARM1CBpBtN1QC7vx9X2n6bwsj3wsikv7ef14CYK9evW7IvcvyTQANqFRiIYBwgQEU4DC/Q+LxOwACIsIJ9ZyZmWmkHsICCPmNV2DGgOQzEIalgtevX+8HcNcfHpYmv/7nDRmfI+8/L61GBUtAtgKxJbI9gATkj7kfgC1evNjE9DE0qlWrZlQr4VaAVAODz0S8FixYYKRhy5YtzTkkqvA9khMQieVz3bAAZHG6quDdL/eTxs/O9/eAilT94np+Pjp3ogGQ/z7KsWPH7EL1yLJnrq4AIrWAbNasWWZu16pVK2PVYnAgyXhFEnIMUPGKz5hxUg4wWICWY1HBbLPCcWxSELIKRrf7AZzWTxqNm1eiWG4okZDAWDAAth79J5NJowA++GDRgwhtiVwPACAqmPECsHfffddkPOG7w+2Cuq1Vq5Z/DkjaHbCifjmPyBnXADT2eNy6davxGaOaR4wYYa4RlhFCBgsF0btnWn9pOG5u5FofcOVj835jACS/UAHs06fPDbl3Wb4JBgZ/6nCeOnWqUauoTYwM1OoXX3xhIENFk27XuHFj8z2MkL7HucCIv5A5I98jRUePHm3ADAtAHtelEnDffw2U+mP/cUPG5/j8314C4EMPPXRD7l2WbwJ8wIVUAxz8vdgBfEcqHg+gnDZtmtkpjfEAMN4zD2Tuh9SbP3++cdcAG/CiljEghw0bZiQg0jBkFYx1oxIQAOs+/fcbMj4ZC16QNk/PNM/9VQnYt2/fG3LvsnwTBZD5HhKOjPjp06cbvy+xeOaCOJ15iipzO6ZNGBnM8TA0OIdzKRglJDBzDPM+NjhFOoYF4IoVK/wA7p8+SOqMmmMoZnIZTiGkdqWdthDfF8cHf/zniwZA/rsonEsDbIlsDwSqYFwtqN1nnnlGmH+TVMw4aMQDycbYIe14j5rFaERaYqiggps0aWLOIYgAqMBY3LZ/l6wJUQmYOn2wpPxqtvlvYDJ6ccH/w8256cWF/wp8SprdEvg7lWKzy8By4oOXLgGQh2HbEtkeAEB8gYwJkg6wgIpH9KKCSUBWVwxCBRYAEiOEODHn4IJBoOA3RCKilu+44w5zzbABZIERJ3HTA68OkZoj/2ZE7OVAojLofBpxcaGSNEQjGxcDyPU16sJc4czHv5c2Y2aahnN//ov69+8f2d63V/e7YTTLhf7HFYc0JBkEo5CQHLAR6WCKpMkK6j8EPmLAjBmvzZs3N9JTd90tTnsGSUDCMCoBD84YKjWe+qupAA7KcErTpk2v+KgGKkSlmfA+8sgj0qFDB8lcOMkPoKrggQMHhnNLe2wJekBjweo2AzDW9AAg1ivCBTcM6hU1qypWH+3bsGFDAzGwITH37t1rEokRIvr0+rAAZOUbhQln2oyfSfUn3zG74vMZuovzaofbByrOTy+aegmAgwYNCvdy9vgwewAAid9qDh9ajY3qyQv94IMPjFGBhiK+i30ATBgYum844BH9QJsBMQJFH3quAGKsXK0EScAvv/zSD+ChPz4isYOnmxui8zX2xwGoVkxxHI/8pyCiqQiQajxRQ2nMDTAucFAGFuBjERQVPLf4Zblt7J9Nug+F+QaPgLAlsj0AfDigNRmV1yVLlhjXCvM/gFLVq/48DBEMUyQiACItyZ4B1kcffdQfsuN3oAxLAi5btswP4NH/Hip5vSdLxolMs/gcnxDQKYDcmJghVhERFN1J//PPPzffIZrJaNHkRp0TcD6NAD4V4ec+niytxvwlCEC7YXlk4ePqSEAA1DkgrziXWRNOaA21ynwOOwBjAxhZosuYMr6ACKhcY9y4cf6ICdfWZ8/gOwxZAkIy4hiVm/tGf9n3L+MkpmItc1PgZG5H4eZqSLRp08ZMVtkJgfcYH5joFOYKzPdWrlxpJrWcg8RT+Kh8YYFXOmyYLL5ffuIHEBFvAYw8gEhA/ijAx3gB08SJE43W0rkh8zqMQhKW8evhrsFixj5A85GMCqy8RxDp9fgclgR87733/AHl/D8NkCo1asuymoNEYhONdXO1AlzAVtxO++q8xIIm9tv17P9K1bSv5PhTX5lJLIVG2EVJkQdQ54CaCc0dGZcZM2YYQURWOlqOKRbTLqQZkpCYMNMkNB2qF8nIPFE3LdD5H9fFLROyBFy4cKG5KMtKGu6YLSmHvxavL0rW5aXIycKEkHqk+KeDFF0m3uOVdvHpkuTJF0+tZrK728sGXqQfjwQj5mhLZHsAaad+QM0JRApi9c6dO9fEfpGQaERg4hjyBYCTOT0eDM7HOuazAqg+QF7DApCbYIhgjiNe+W8IN7OlJF1Go5kj0hAaraq+JNey54TeAxe7YXRXC7TZ5MmTzXyQuSDGpfp9gQzhwBgxVky9eHYgxia/qQtGs53CCsWFXnV7pBt6AADVoRy4DJM53pNPPmnm8ggGtBKqGBWMykXaEWLDk4G0ZJ4HkDr/U7cOfRRWNowbOtW2IfQewNGsfkCkH0YGHg+iIcDEPA+A0Ib8ToII0g+JqOFZjBE+qw2A1sQW4HdUdlgJqaFX3R7phh7QNSEYGbjSkIZ4NIAK4HiGIDChRh977DHjwcD1glpmbqcPONesaeCjcF2kI1EUC6AbSIlQG5CABBgIHjDHAyysXLwTqFEkIYYKHhDm50g/fIKoYuZ8gAqgmr6va0t0twXgK86YtHtER2hwnXBZJB4JCBpaAzqiW8z7gBAo1aGMdOMPi5i0fVQuKlah4zNGCJ85n1ekYHHuOwugE0iJUB1JpWdxEa+6wByjAoBQo7jkMDgIkSLlkHb8pvFd5nlAqWE3XoFSvRqobisBIzR4brgsMGF0qOMYKYZa1vR6VDJhU6QeBglgAaIuzVSpB3SAqL5EjmGuSFIqTuqrFSsB3UBSCdsAKBgfgEThs+5yy3sNz+l+MECo639Rz/6wbW6uAZASmFvIuhHi/RbAEg6Q209D0rHRPKqUPyQiYKkRAYy8B0DUtEpGVK3O93TXBMBTVQy8qO2uXbuGFwt2e4fb9gX3ACpWLWCkoO4BqKE0VDOqVGEDLEDVfQH1amqIBJ5PXB8AL360x8VjYFVwGaYSKxijg8iHyQG4sDYkMCqi0OmuCLoEk27TjSo5RveCQSICKcYNTzoIKxZchseiTDYdAPHlkemCmmUeh7RTY0LzAAJVM5JSM6EDd01Vdc25QI0FjLvGAlgm0Qqt0Vi8uquBGhSB0KkRorFdgAPSQBWsSQdIQM2UXrRokYwcOdKAGtayzNCqbY9ySw/oumCsW96TcIBaBTAFiraqpAMoVDCfkXioXrV++Y45JSl1OLGJGwNnWAmpbulY247QeiBwZwTSqoAFwJBkgAVwzP00TAdQzO807Yrf+cwcEhg57q233pIJEyYY1w4SNKyU/NCqbY9ySw+oCkbqsdNV4Ebk6pYJdC4DFIBq4imfdVsPJOa8efOM34+t2YAVqWgBdAstEWiHAggoxINZB0Jqleb/AZo6l9XxDKxIPH5TNcx5AIcUHT9+vP9Rbnxn3TARGDi3XBLppZsLqVtFHcqB6zoC/X1qdPCdvlcjJfDZgPr75bZ1Cew/6wd0C00ObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55ZqWwDdMpIObYcF0KED55Zq/x974mJc7RaYhAAAAABJRU5ErkJggg==.Encode is the procedure nam, and it has two parameters text and shift #

For = a loop

110i

encode is the procedure with two parameters. char and shift

32

4.2.2 ITIT 5

As the lab says, it's okay to use ">" and "<" instead of "≥" and 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AAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECByxcQFpoRMBzwAAAABJRU5ErkJggg==Encipher or Decipher?1DoutputTextD]r]jke_a`]eHav a noice dai-4