Mediterranean journal of basic and applied sciences最新文献

{"title":"Low Power Scan-based Built-in Self-test Based on True Random Number Generator Using Multistage Feedback Ring Oscillator","authors":"None Suba, P., None Arivazhagan, P., None Stalin, A.","doi":"10.46382/mjbas.2023.7309","DOIUrl":"https://doi.org/10.46382/mjbas.2023.7309","url":null,"abstract":"A new low power scan-based built-in self-test (BIST) technique is proposed based on weighted pseudorandom test pattern generation and reseeding. A new LP scan architecture is proposed, which supports both pseudorandom testing and deterministic BIST. During the pseudorandom testing phase, an LP weighted random test pattern generation scheme is proposed by disabling a part of scan chains. During the deterministic BIST phase, the design for testability architecture is modified slightly while the linear feedback shift register is kept short. In both the cases, only a small number of scan chains are activated in a single cycle. Sufficient experimental results are presented to demonstrate the performance of the proposed LP BIST approach. This Proposed design will be implemented by Verilog HDL and simulated by Modelsim Tool.","PeriodicalId":485573,"journal":{"name":"Mediterranean journal of basic and applied sciences","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136373365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Fertilizer Recommendation System for Disease Prediction Using Deep Learning Algorithm","authors":"None Mahishanthini M., None Arivazhagan, P., None Stalin, A.","doi":"10.46382/mjbas.2023.7307","DOIUrl":"https://doi.org/10.46382/mjbas.2023.7307","url":null,"abstract":"In addition to providing food for a growing population, agriculture also helps to combat global warming and is a source of energy. Because they may have a detrimental effect on the type and quantity of produced in agriculture, plant diseases are particularly significant. Identification of plant diseases at an early stage is essential for treatment and crops disease management. To identify ailments, people frequently use their naked eyes. This technique involves experts with the capacity to spot variations in leaf colour. This process is labor-intensive, time-consuming, and unsuitable for large fields. Multiple medical experts would frequently give various diagnoses for the same illness. Due to the ongoing need for professional supervision, this technology is expensive. Plant diseases can increase the cost of agricultural output and, if left untreated, can completely bankrupt a company. To control the spread of a plant disease at a low cost and save the bulk of the harvest, growers must keep an eye on their crops and be able to identify early indications. Expert agriculturists may be excessively expensive to hire, especially in rural and inaccessible regions. An alternative way to plant monitoring can be provided by a deep learning algorithm embedded in a picture, and this method can be managed by a specialist to offer less expensive services. It includes features extraction and classification, as well as an image classification method that anticipates several illnesses in maize leaf using a neural network approach. Additionally, adapt the method to prescribe fertilizers based on severity analysis and data.","PeriodicalId":485573,"journal":{"name":"Mediterranean journal of basic and applied sciences","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135007038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lived Experiences of Police Officers in the Implementation of Operational Plan Against Illegal Drugs","authors":"Bryan E. Fuentes, Jayvee B. Gengania, Kim August A. Malon, Kit Lorenz U. Mayol, Elmie A. Allanic, Jose F. Cueva","doi":"10.46382/mjbas.2023.7304","DOIUrl":"https://doi.org/10.46382/mjbas.2023.7304","url":null,"abstract":"Illegal drugs pose a pervasive and longstanding problem in the Philippine Archipelago, requiring the efforts of law enforcement agencies to combat their proliferation. This study focused on exploring the lived experiences of Philippine National Police (PNP) personnel in dealing with the challenges associated with illegal drugs, specifically in the context of Ozamiz City. Through interviews with five police officers, using a research-made interview guide and applying Moustaka's Transcendental Analysis, the study revealed four main themes: compromised personal and family security, the need to suppress crime escalation, resistance from suspects, and the dilemma of conducting surveillance. The findings of this phenomenological study underscore the multitude of challenges faced by police officers in their mission to combat illegal drugs. One significant challenge is the compromise of personal and family security, as officers are often exposed to threats and retaliation from individuals involved in the drug trade. The escalation of crime resulting from drug-related activities further emphasizes the urgency for law enforcement to suppress this issue from the community. However, officers encounter resistance from suspects who are unwilling to cooperate and may resort to tactics that jeopardize the safety of the officers' families. To address these challenges, police officers should prioritize through surveillance to gather accurate information on suspects and their activities. This entails utilizing available resources and collaborating with other agencies and stakeholders to gather the necessary intelligence. Additionally, ensuring officers' personal and family security should be a paramount concern, with appropriate measures in place to safeguard their well-being.","PeriodicalId":485573,"journal":{"name":"Mediterranean journal of basic and applied sciences","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135498064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tales of the Soldiers in the Middle of Armed-Conflict: Phenomenological Study","authors":"Vegie S. Naranjo, Mark Lester Quiap, Julius Taylaran, Jeffrey Tierra, Jose F. Cuevas","doi":"10.46382/mjbas.2023.7305","DOIUrl":"https://doi.org/10.46382/mjbas.2023.7305","url":null,"abstract":"The experiences of Filipino soldiers in this study will be able to help current service members, those thinking about a military career, as well as the general public. It examines the definition of \"soldier\" across numerous militaries and the various military careers that call for certain knowledge and skill sets. The difficulties that troops undergo include long separations from their families and ongoing danger. Specifically, armed conflicts in the province of Misamis Occidental in the Philippines highlight recent clashes between the Philippine Army and the New People's Army (NPA) rebels. This study aims to determine the profile of the soldiers in terms of age, sex, rank, and social status, and to explore the experiences of soldiers in the middle of armed conflicts. This study used the phenomenological design method of qualitative research to examine how Filipino soldiers felt while carrying out their tasks and responsibilities. The data analysis procedure followed Moustakas' transcendental phenomenology and sought to identify significant themes and essences generated from the participants' experiences. The study was conducted in Region X, Misamis Occidental, Philippines with five participants who are all experienced Filipino soldiers. The researchers interviewed the said participants, all of which are from Misamis Occidental, Philippines, with an average service in the military of at least three years. The participants were interviewed in their homes, observing proper health protocols given the Covid-19 strain. During the interview, the soldiers stressed the difficult nature of counterinsurgency deployments, emphasizing the need for protection through alertness, cooperation, and prayer. Because of their sense of purpose and desire to protect their family and serve their country, they demonstrated great intrinsic motivation and steadfast dedication. In conclusion, military operations faced demanding circumstances, requiring them to be vigilant and collaborate while seeking protection through prayer. Although they encountered risks, many expressed gratitude for minimal casualties and the challenging nature of counterinsurgency deployments. Teamwork and unity were crucial during these deployments, with coordination and cooperation among soldiers playing essential roles in navigating hostile environments.","PeriodicalId":485573,"journal":{"name":"Mediterranean journal of basic and applied sciences","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135914558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Fatal Vehicle Collision Avoidance System for the Deterrence of Mishaps in Potential Zones","authors":"None Jayashree, C., Navaneetha Krishnan, P., None Kuralamudhu, K.","doi":"10.46382/mjbas.2023.7310","DOIUrl":"https://doi.org/10.46382/mjbas.2023.7310","url":null,"abstract":"Road traffic sign detection is an important task for ensuring road safety. In our day today life, time is very important thing so everyone trying to complete the task in less time is the human tendency. Therefore to complete the desired task as early as possible we should increase the speed, for example speed of vehicle. Road traffic sign detection is a challenging task that has been the subject of research for many years. The detection of road signs is essential for ensuring the safety of drivers, pedestrians, and other road users. As well as the drivers are not following the rules and regulation given by traffic control department at specific areas. But most of the drivers drive the vehicle very fast in that restricted areas with and without reasons. Existing systems for road traffic sign detection often rely on traditional computer vision techniques, such as template matching and feature extraction. These techniques are limited in their ability to detect signs in different lighting conditions and may not be able to identify signs with occlusions. Moreover, existing systems may not be capable of detecting different types of zones, such as school zones, hospital zones, and accident zones. The proposed system uses a CNN algorithm for real-time road traffic sign detection. The system consists of three main stages: image acquisition, sign detection, and sign classification. In the first stage, the system acquires an image of the road scene using a camera. In the second stage, the system uses image processing techniques to detect road signs in the acquired image. The system then extracts features from the detected signs and uses a CNN algorithm to classify them according to the three different types of zones: school zones, hospital zones, and accident zones. The proposed algorithm can be used as an effective tool for real-time road traffic sign detection, particularly for detecting school zone, hospital zone, and accident zone signs. The algorithm's accuracy and efficiency make it suitable for use in various applications, including autonomous driving, traffic monitoring, and road safety.","PeriodicalId":485573,"journal":{"name":"Mediterranean journal of basic and applied sciences","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136373640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A System for Diagnosing Alzheimer’s Disease from Brain MRI Images Using Deep Learning Algorithm","authors":"None Neelavathi, S., None Arunkumar, P., None Janani, K.","doi":"10.46382/mjbas.2023.7308","DOIUrl":"https://doi.org/10.46382/mjbas.2023.7308","url":null,"abstract":"In addition to their vulnerability, the complexity of the operations, and the high expenses, disorders of the brain are one of the most challenging diseases to treat. However, because the outcome is unpredictable, the procedure itself does not need to be successful. One of the most prevalent brain diseases in adults, hypertension, can cause varying degrees of memory loss and forgetfulness. Depending on each patient's situation. For these reasons, it's crucial to define memory loss, determine the patient's level of decline, and determine his brain MRI scans are used to identify Alzheimer's disease. In this thesis, we discuss methods and approaches for diagnosing Alzheimer's disease using deep learning. The suggested approach is utilized to enhance patient care, lower expenses, and enable quick and accurate analysis in sizable investigations. Modern deep learning techniques have lately successfully demonstrated performance at the level of a human in various domains, including medical image processing. We propose a deep convolutional network for diagnosing Alzheimer's disease based on the analysis of brain MRI data. Our model outperforms other models for early detection of current techniques because it can distinguish between different stages of Alzheimer's disease.","PeriodicalId":485573,"journal":{"name":"Mediterranean journal of basic and applied sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135007249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote Sensing and Geographic Information System (GIS) Contribution to the Inventory and Investigation of Dikes in Egypt","authors":"Barbara Theilen-Willige","doi":"10.46382/mjbas.2023.7306","DOIUrl":"https://doi.org/10.46382/mjbas.2023.7306","url":null,"abstract":". ABSTRACT Dikes are widespread in Egypt and are partly even the prevailing elements in the landscape besides the youngest sedimentary covers, especially in the southern and eastern part of the country. Although dikes are one of the predominant phenomena in Egypt, a systematic, standardized inventory of dikes in the whole country and a dike data base has not been published so far, although several selected areas have been investigated very detailed such as along the Red Sea and in the Sinai. Remote sensing and Geographic Information System (GIS) offer tools for such an inventory. This inventory is of interest for many purposes such as for the mining industry (many dikes are related to mineral occurrence of economic value), and also for hydrogeologic investigations and land use planning. Surface-near dikes, major fault zones, volcanic and structural features were digitized based on Landsat 8 and 9, Sentinel 2, Sentinel 1 and ALOS PALSAR data. High resolution images of World Imagery files/ESRI and Bing Maps Aerial/Microsoft were included into the evaluations. More than 32,000 dikes were digitized and analysed. The evaluations of satellite images allow a geomorphologic differentiation of types of dikes and the description of their characteristics such as dike swarms or ring dikes as well as of their distribution pattern and orientations. Dike density calculations were carried out in ArcGIS to support the detection of areas with dike concentrations. Earthquake data were included into the investigations as dikes might play a role in the development and effects of earthquake swarms in the area of reservoirs.","PeriodicalId":485573,"journal":{"name":"Mediterranean journal of basic and applied sciences","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135914247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}