The Comprehensive Review of Neural Network: An Intelligent Medical Image Compression for Data Sharing

In the healthcare environment, digital images are the most commonly shared information. It has become a vital resource in health care services that facilitates decision-making and treatment procedures. The medical image requires large volumes of storage and the storage scale continues to grow because of the advancement of medical image technology. To enhance the interaction and coordination between healthcare institutions, the efficient exchange of medical information is necessary. Therefore, the sharing of the medical image with zero loss of information and efficiency needs to be guaranteed exactly. Image compression helps ensure that the purpose of sharing this data from a medical image must be as intelligent as possible to contain valuable information while at the same time minimizing unnecessary diagnostic information. Artificial Neural Network has been used to solve many issues in the processing of images. It has proved its dominance in the handling of noisy or incomplete image compression applications over traditional methods. It contributes to the resulting image by a high compression ratio and noise reduction. This paper reviews previous studies on the compression of intelligent medical images with the neural network approach to data sharing

A review on region of interest-based hybrid medical image compression algorithms

Digital medical images have become a vital resource that supports decision-making and treatment procedures in healthcare facilities. The medical image consumes large sizes of memory, and the size keeps on growth due to the trend of medical image technology. The technology of telemedicine encourages the medical practitioner to share the medical image to support knowledge sharing to diagnose and analyse the image. The healthcare system needs to ensure distributes the medical image accurately with zero loss of information, fast and secure. Image compression is beneficial in ensuring that achieve the goal of sharing this data. The region of interest-based hybrid medical compression algorithm plays the parts to reduce the image size and shorten the time of medical image compression process. Various studies have enhanced by combining numerous techniques to get an ideal result. This paper reviews the previous works conducted on a region of interest-based hybrid medical image compression algorithms

Diversity and guild structure of insects during rice flowering stage at a selected rice field in Penang, Malaysia

A study on diversity of insects in rice field was conducted at Kg Terus, Guar Perahu in Penang. This study aims to determine the diurnality and guild structure of insect in rice field specifically during the flowering stage of rice. Insects were collected using sweep net method and light trap method. Overall, a total of 1936 insect specimens representing 28 species, 19 families and seven orders were collected. Twenty five species from 19 families were caught during day time while 17 species from 13 families were trapped at night. Coleopterans were the dominant insect captured during day time sampling with Micraspis crocea from family Coccinellidae captured in highest number (223). In contrast, Hemipterans was dominant during night time with Nilaparvata lugens from family Delphacidae found in highest number (258). The Odonata recorded the highest diversity index (H’= 1.2587) while Coleoptera recorded the highest richness index (Imargalef = 5.8390) values for diurnal insect. For nocturnal insect, Hemiptera recorded the highest values for both diversity index (H’= 1.2655) and richness index (Imargalef = 5.8390). In term of guild structure, the rice pest was the most dominant insect found in rice field for both diurnal and nocturnal group. This followed by predator, others (visitor/pollinator) and parasitoid groups. Result of this study will identify the classification of insect present during the flowering stage of rice allowing farmers to forecast pest population build up to assist in the pesticides selection that will be generally applied at the end of flowering stage. This consequently will help to conserve beneficial insects and lower the pest management cost

Integrating cleaning studies with industrial practice: case study of an effective cleaning program for a frozen meat patties SME factory

Cleaning of process equipment is a necessity in the food industry. There is no standard cleaning program formulated for all food industries. Thus, in order to achieve economic objectives and to comply with food hygiene regulations, specific cleaning problems need to be solved to achieve an optimal solution. In this work, a cleaning program was proposed for a local frozen meat patties Small and Medium Enterprise (SME) factory, X. Several cleaning tools such as a portable cleaning unit and industrial cleaning brushes with different functionality were used to ensure the effectiveness of the cleaning program. The portable cleaning unit was used to evaluate the impact of water jet with different nozzle distances (10 cm and 20 cm), cleaning times (30 s and 120 s), and temperatures (35 °C and 65 °C) in reducing different foodborne pathogens (Escherichia coli, Listeria monocytogenes, and Salmonella enteritidis). Two places of food processing equipment with two different stainless steel surfaces were tested. First, a former of meat patties (mesh wire surface), and second, a mixer (smooth surface). The results were then compared with factory X's current cleaning program and have shown that this new cleaning program can achieve physical clean level and helped to reduce microorganism to non-detectable level (less than 2.0 CFU/cm2). For the evening cleaning, the suggested cleaning program is using the portable cleaning unit at 65 °C, 120 s, 10 cm nozzle distance, and 5.2 bar. For the morning cleaning before production, the same parameters are suggested except for the temperature which is slightly higher at 75 °C

A Built-In-Self-Test Arithmetic Logic Unit (A BIST ALU) / Suhaila Ab. Aziz

Perkembangan pesat teknologi. litar bersepadu telah merintis kepada perkembangan pembinaan litar sersepadu berskala besar (Very Large Scale Intergrated Circuit - VLSI). Dalam usaha meningkatkan prestasi, dan kebolehpercayaan litar-litar VLSI yang dibangunkan, pembangun perlulah memastikan ia bebas daripada sebarang bentuk kecacatan atau ralat. Ini merupakan pendorong kepada perkembangan kaedah Design For Testability (OFT) yang berfungsi untuk. membantu para pembangun bagi kecacatan litar. Built-Jn-Self-Test (BIST) merupakan salah satu teknik yang menggunakan konsep menggabungkan litar ujian bersama litar yang sedang diuji. Matlamat utama BIST adalah untuk mengurangkan pergantungan litar yang direkabentuk kepada penguji dan memperoleh kemudahan ujian pada kelajuan operasi kelajuan sistem dengan liputan kegagalan yang tinggi. Ia meliputi tiga fungsi utama iaitu; penjanaan vektor ujian, penggunaan vektor ujian dan analisis pengenalan (signature analysis). Sebagai permulaan kepada pembangunan BIST, 8 bit Arihtmetic logic Unit (ALU) telah digunakan sebagai litar untuk diuji

Peroxidase Activity after Viral Infection and Whitefly Infestation in Juvenile and Mature Leaves of Solanum lycopersicum

Whitefly infestation and the begomoviruses that they transmit have been shown to affect the activities of plant defence proteins, but with no relation to heterophylly, a process of great importance underlying the overall biology of plants. Here, we have assessed the effects of Tomato yellow leaf curl virus (TYLCV) infection on Solanum lycopersicum peroxidase (POD) activity and have examined whether leaves of different ages exhibit differential POD activity in response to infection and infestation with Bemisia tabaci B biotype. We used leaf discs of two ages (juvenile and mature) with two different infection statuses (infected and healthy) to examine the activity of the tomato plant peroxidase using guaiacol as a substrate and taking exposure time into account. S. lycopersicum showed increased POD activity in the presence of TYLCV. The activity of the enzyme was higher in mature than in juvenile leaves. In general, both infected and healthy leaves exhibited greater POD activity during whitefly infestation. In the infested juvenile leaves, POD activity was much lower in the healthy leaves and increased gradually with period of exposure to B. tabaci B infestation. In contrast, the activity of the enzyme remained low in infested mature leaves in both the presence and absence of the virus even with increased exposure time. Determination of the distribution of an insect pest is critical for sampling and management. Leaf age is presumed to be associated with the within-host distribution of the geminivirus vector B. tabaci. Juvenile leaves will usually attract more insects due to increased nutritional value and weaker defences. Our results highlight the importance of leaf age/position on the whitefly – host plant – geminivirus interactions and have important implications for sampling and control strategies

A Performance Review for Hybrid Region of Interest-Based Medical Image Compression

In this modern era, medical image sharing has become a routine activity within hospital information systems. Digital medical images have become valuable resources that aid health care systems’ decision-making and treatment procedures. A medical image consumes a significant amount of memory, and the size of medical images continues to grow as medical imaging technology progresses. In addition, an image is shared for analysis to support knowledge sharing and disease diagnosis. Therefore, health care systems must ensure that medical images are appropriately distributed without information loss in a timely and secure manner. Image compression is the primary process performed on each medical image before it is shared to ensure that the purpose of sharing an image is accomplished. The hybrid region of interest-based medical compression algorithms reduces image size. Furthermore, these algorithms shorten the image compression process time by manipulating the advantages of lossy and lossless compression techniques. A comprehensive review of previous studies that utilized this approach was conducted. Sample studies were selected from published articles in an open database subscribed to by Universiti Teknologi Malaysia for ten years (2012 to 2023). This work aims to critically review and comprehensively analyze previous types of algorithms by focusing on their main performance results: compression ratio, mean square error and peak signal-to-noise ratio. This article will identify which type of algorithm can give optimal value to the primary performance metric for compressing medical images