A Systematic Review of Tracing Solutions in Software Product Lines

Software Product Lines are large-scale, multi-unit systems that enable massive, customized production. They consist of a base of reusable artifacts and points of variation that provide the system with flexibility, allowing generating customized products. However, maintaining a system with such complexity and flexibility could be error prone and time consuming. Indeed, any modification (addition, deletion or update) at the level of a product or an artifact would impact other elements. It would therefore be interesting to adopt an efficient and organized traceability solution to maintain the Software Product Line. Still, traceability is not systematically implemented. It is usually set up for specific constraints (e.g. certification requirements), but abandoned in other situations. In order to draw a picture of the actual conditions of traceability solutions in Software Product Lines context, we decided to address a literature review. This review as well as its findings is detailed in the present article.Comment: 22 pages, 9 figures, 7 table

The Future of Tax Reform: A Rejoinder to Professor Zelinsky

Optical character recognition (OCR) is a fundamental problem in computer vision. Research studies have shown significant progress in classifying printed characters using deep learning-based methods and topologies. Among current algorithms, recurrent neural networks with long-short term memory blocks called RNN-LSTM have provided the highest performance in terms of accuracy rate. Using the top 5,000 French words collected from the internet including all signs and accents, RNN-LSTM models were trained and tested for several cases. Six fonts were used to generate OCR samples and an additional dataset that included all samples from these six fonts was prepared for training and testing purposes. The trained RNN-LSTM models were tested and achieved the accuracy rates of 99.98798% and 99.91889% for edit distance and sequence error, respectively. An accurate preprocessing followed by height normalization (standardization methods in deep learning) enabled the RNN-LSTM model to be trained in the most efficient way. This machine learning work also revealed the robustness of RNN-LSTM topology to recognize printed characters

Retaining force augmentation of retaining walls

Concrete blocks retaining walls are commonly used for landscaping projects in which the retaining force strength of the structure is of paramount importance in preserving the integrity of the project and safety of humans and property. The effect of augmenting the retaining force strength of concrete block retaining walls was investigated using interlocking and interlocking with a horizontal steel re-bar and compared with regular concrete block walls. The average maximum retaining force for regular, interlocking and interlocking with horizontal rebar walls was 16862 N, 24546 N, and 80855 N at wall deflection of 12.2 mm, 13.3 mm and 50.7 mm, respectively. The average maximum retaining force of the interlocking and the interlocking with horizontal re-bar walls increased by 45.6 % and 379.5 %, respectively, when compared to regular concrete block walls. The inclusion of a horizontal steel re-bar in the interlocking design showed an increase of 229.4 % in the retaining force strength. The wall sections without the horizontal re-bar failed abruptly beyond the maximum retaining force for both the regular and interlocking blocks. The interlocking concrete block design and the inclusion of a horizontal steel re-bar both significantly augmented the retaining force strength of concrete block retaining walls

Research on Application of Cognitive-Driven Human-Computer Interaction

Human-computer interaction is an important research content of intelligent manufacturing human factor engineering. Natural human-computer interaction conforms to the cognition of users' habits and can efficiently process inaccurate information interaction, thus improving user experience and reducing cognitive load. Through the analysis of the information interaction process, user interaction experience cognition and human-computer interaction principles in the human-computer interaction system, a cognitive-driven human-computer interaction information transmission model is established. Investigate the main interaction modes in the current human-computer interaction system, and discuss its application status, technical requirements and problems. This paper discusses the analysis and evaluation methods of interaction modes in human-computer system from three levels of subjective evaluation, physiological measurement and mathematical method evaluation, so as to promote the understanding of inaccurate information to achieve the effect of interaction self-adaptation and guide the design and optimization of human-computer interaction system. According to the development status of human-computer interaction in intelligent environment, the research hotspots, problems and development trends of human-computer interaction are put forward

Analysis and Detection of DDoS Attacks Using Machine Learning Techniques

Over the past years, distributed denial-of-service (DDoS) attacks on Internet services and websites have dramatically increased. Several research teams designed defensive methodologies to handle the DDoS attacks. Using machine learning-based solutions have enabled researchers to detect DDoS attacks with complex and dynamic patterns. In this work, a subset of the CICIDS2017 dataset, including 200K samples and 84 features, was used to analyze the features and build models. A correlation analysis, as well as a tree-based feature importance exploration, were performed in the feature engineering step. Next, decision tree and support vector machine models were trained and tested to classify DDoS and Benign attacks. The results revealed that “Flow ID,” “SYN Flag Cnt,” and “Dst IP” had the most impact on attack detection. Also, the machine learning models classified the DDoS attacks, where the accuracy rates of close to 100% were achieved. The decision tree models showed slightly better performance than linear support vector machines. The results in this work highly matched the outcome of the original paper, which was to replicate

Flexural Tensile Strength of Asphalt Composites with Calcined Clay under Four-Point Bending

Replacing natural aggregates for employment in pavement applications has been exhaustively proposed in order to reduce the unsustainable consumption of these materials. An option widely studied in the Amazon Region is the Sintered Calcined Clay Aggregate (SCCA), a promising alternative to the historical scarcity of rocky material, given the region geology, primarily for the strong occurrence of clays. The aim of this research is to study the use of calcined clay aggregates to create an alternative mixture for asphalt coating of urban paved roads. The influence of temperature variation on the mechanical behavior of SCCA asphalt concrete was also evaluated in order to simulate high-temperature zones. Four-point bending tests were performed on prismatic specimens compacted in controlled conditions with the aim to determine the Flexural Tensile Strength. Superpave method was used for the design of asphalt mixes. The test results from this study indicated that the FTS increases with frequency and decreases with temperature. On the other hand, increasing temperature promotes a tendency of stabilization of the FTS, in which the saturation of the asphalt binder can be observed, due to its viscoelastic nature

Correlating Antiretroviral Therapy Adherence and Detection of HIV Viral Loads at Chitipa District Hospital

HIV infection remains an epidemic threat around the world mostly prevalent in developing countries especially in sub- Sahara African region where many cultural practices and beliefs aggravate the transmission of HIV/AIDS. Poor Antiretroviral therapy (ART) adherence remains a big challenge leading to persistence detection of high HIV viral load results which deteriorate PLHIV health through lowering immunity [1]. This study aimed to determine the correlation of ART adherence with high detection of viral load levels among HIV patients receiving ART at Umoyo ART clinic (Chitipa DHO) in Chitipa district. A retrospective study design using PLHIV records, on HIV viral load results in viral register and ART adherence percentage (based on number of days missed to collect ARV drugs) using Electronic Medical Records (EMR) system between January, 2018 and December, 2018. There were 3890 patients registered alive on ART but 2835 patients had their viral load results in register.  Therefore, 351 sample records were extracted using systematic sampling technique and analysed using statistical package for social sciences (SPSS) version 20. The findings showed that 37.7% (n=131) of HIV patients in the study had detectable viral load after a duration of over six months on ART and more experienced in 80/200 (42%) of patients with good adherence. However, poor ART adherence (˂95%) more prevalent in men, youths and HIV patients less than five years on ART. Pearson’s Chi square test indicated a statistical significant on correlation between age and ART adherence as well as ART adherence and HIV viral load results (p<0.05). On the other hand, gender and duration on ART were not significant to ART adherence level. Eventually, it is recommended more ART clerks should be recruited so that any HIV individual initiated on ART should intensively counselled on poor ART adherence which may lead to development of HIV drug resistance strains that need expensive second and third line regimen ARV drugs

Decolorization of Textile Effluents Applying Sequential Operation of Prepared Activated Carbons

Three activated carbons were prepared from bio-waste material and their adsorption efficiency in removal of textile effluents was tested. During sequential operation of these carbons, textile effluents were decolorized with better results like 7, 5 and 3 m-1 absorbance at wavelengths of 436, 525 and 620 nm respectively. 2 g of each adsorbent and at optimum contact time of 40 min removed 93% of color form collected textile effluents

Single Device that can Measure Gravity, Magnetism & Data for Inertial Navigation System and Also Provide Propulsion to Satellites for Prolonged Missions in Space

The paper proposes workable ideas for development of a single device that can measure values of Gravity, Magnetic Fields and changes in Angular and Linear velocity of a vehicle to be used for inertial navigation system. Moreover, the same device can also be used as in-space propulsion system for satellites that can sustain operations indefinitely; thus paving way for miniaturization of satellites in order to achieve cost effectiveness and prolonged life time of satellites in space, by eliminating the need of propulsion fuels. The system will be powered by onboard solar panels. This will enable not only missions around earth, moon or nearby planets but also deep space missions around solar system as long as power source remains viable. The device utilizes magnetic levitation achieved through combination of permanent and electromagnets whereby momentum of a ball magnetically suspended inside a spherical electromagnet is transferred to satellite due to its acceleration under magnetic forces to provide propulsion. The linear and angular displacements of the inner suspended ball provide data for inertial navigation and measurement of gravity and magnetic fields

Feet Microbial Infections

Microbial foot disorders are quite common around the globe. People who usually don’t take care about their foot hygiene and overall health often suffer from serious foot ailments. Causes of these disorders may be poor cleanliness, diabetes miletus, improper foot ware and socks use.  Among them, shoes and socks as remain moist due to sweat and dirt, are a potent source of microbial invasion which may be either of bacterial, fungal or viral origin, sometimes algal too. People of third world countries are more prone to such disorders because of lack of awareness. These issues can be controlled by introducing proper general mass awareness regarding foot care and hygiene and by spreading information regarding foot ulcers and wounds handling to medical staff and common people