Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges and Opportunities of MSEs in Ethiopia: A Review Paper

The micro and small business sector is recognized as an essential component of economic development and a crucial element in the effort to lift countries out of poverty (Wolfenson, 2007). External and internal factors are known to affect the growth of MSEs. Thus, this review provides overview of challenges, prospects and factors affecting growth of Micro and Small Scale Enterprises (MSEs). “Google Scholar” and “Science direct” search engines/databases were used to conduct the review using search keywords ‘’the challenges of MSEs’’, ‘’the achievements of MSEs’’ and, “factors affecting MSEs growth’’. The 16 articles collected show that The prominent challenges listed in various studies in Ethiopia are access to finance, selling at less price compared with other similar enterprises, shortage of raw material, lack of experience in own business, limited access to markets, to premise, lack of training, cultural oppressions, high competition as a result of open entry to the business, development strategy and policy focusses on agriculture which in turn discourage MSEs operating in other sectors, unattractive market, lack of advertisement, training. shortage of electricity and unscheduled power cuts, bureaucratic working procedure, high tax, high collateral requirement, high interest rate, lack of technology, weak performance leading to absence of growth thinking challenges, starting business without conducting survey, inappropriate tenure, uncollectible receivables, lack of financial management skill and Youth’s adverse attitude towards working under umbrella of MSEs agency. On the opportunity side, studies revealed few of them including business consultation services, training for the beginners, loan facilities, moral or encouragement, peace and security, area specific features, support and reward like training, fund, and certificate play a role for expansion and growth of women entrepreneurs in particular and MSE owners in general. Keywords: Challenges, Growth, MSEs, Opportunities
A Review on Secure Channel Establishment Technique to Increase Security of IoT

: The internet of things is the decentralized type of network in which no central controller is present due to such type of network routing is the major issue. In the previous research various authors has proposed techniques which increase security of IoT. In this review paper, various techniques correspond to security issues are analyzed in terms of certain parameters.
Advanced n Advanced n Advanced n Advanced

Because of the non uniform node distribution, the energy spending among nodes are more imbalanced in cluster-based wireless sensor networks. Based on this problem, in this paper, a cluster-based routing protocol for wireless sensor networks with non uniform node distribution is proposed, which includes an energy-aware clustering algorithm EADC and a cluster-based routing algorithm. EADC uses competition range to make clusters of even sizes. At the same time, the routing algorithm increases forwarding tasks of the nodes in barely covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes as their next hops, and finally, achieves load balance among cluster heads. Theoretical analysis and simulation results show that our protocol can balance the energy spending among nodes and increase the network lifetime considerably.
An Optimal Partition Approach for Mobile to Cloud Offloading

— Now a days smartphones have become an essential part of our life as the most convenient communication tool. The main point of attraction of them is feature rich applications. These applications imply a heavy workload on processors, which causes a significant energy cost as they are battery powered. In this paper, we represent a computation offloading scheme on mobile devices to improve the performance and energy consumption. When a task comes to the mobile device, this scheme partition the task into a client–server distributed program, such that the client code runs on the handheld device and the server code runs on the server. We give optimal partition algorithm to find an optimal program partition for given program input data. Experimental results show significant improvement of performance and energy consumption on an android handheld device through computation offloading.
MULTI SCALE ANALYSIS OF CARDIOVASCULAR VARIABILITY

Cardiovascular variability refers to the beat-to-beat alterations in RR intervals of electrocardiogram (ECG) and a decrease in its value or abnormalities in its patterns have been used as a measure for predicting the future coronary events. Multiscale entropy (MSE) is a will developed complexity measure to quantify the concomitant effect of the cardiovascular regulating mechanisms at different time scales. This paper investigate the performance of MSE to classify the normal healthy and cardiac subjects. Lead-II ECG was acquired from 10 healthy (average age 31 years) and 10 acute myocardial infarction (AMI) subjects (average age 48 years). The study confirms that the time scales has a significant effect on MSE based cardiovascular variability.
HYBRID APROACH FOR WEB PAGE CLASSIFICATION BASED ON FIREFLY AND ANT COLONY OPTIMIZATION

: The rapid development of the internet and web publishing techniques create numerous information sources published as HTML pages on World Wide Web. WWW is now a popular medium by which people all around the world can spread and gather the information of all kinds. But web pages of various sites that are generated dynamically contain undesired information also. This information is called noisy or irrelevant content. The need for innovative and effective technologies to help find and use the useful information and knowledge from a large variety of data sources is continually increasing. Web information has become increasingly diverse. In order to utilize the Web information better, people pursue the latest technology, which can effectively organize and use online information. Classification is one of the vital and important data mining techniques that grouped various items in a collection to predefined classes or groups. The main goal of classification is to exactly predict the target class for each case in the data. Web Page Classification is technique of data mining to discover classification of web pages. The information providers on the web will be interested in techniques that could improve the effectiveness of the web search engine. In this paper, the relationships among the techniques used in data mining are studied. A study of web usage is also done on optimization of this web classification.
A Multi-Authority Access Control System Using Network security: A Survey

: Attribute base Encryption (ABE) is the cryptographic conducting tool to assurance data owner’s enduring control above their data in public cloud storage. The proposed ABE plans include one and only power to keep up the entire trait set, which can carry a solitary point bottleneck on both safety and execution. In this way, some multi-power plans are proposed, in which various powers independently keep up disjoint trait subsets. In any case, the single-point bottleneck issue stays unsolved. In this paper, from another point of view, we lead an edge multi-power CP-ABE access control plan for open distributed storage, named TMACS, in which various powers together deal with a uniform characteristic set. In [9] TMACS, exploiting (t; n) limit mystery sharing, the expert key can be shared among numerous powers, and a legitimate client can produce his/her mystery key by cooperating with any t powers. Security and execution investigation results demonstrate that system is not just undeniable secure when not as much as t powers are traded off, additionally dynamic when no not as a great deal as t powers are alive in the framework. Besides, by proficiently joining the customary multi-power plan with system, we build a half and half one, which fulfils the situation of traits originating from various powers and accomplishing security and framework level strength.
Internet of Things: Opportunities and Future Scope

The Internet of Thing (IoT) is gaining popularity day-by-day and has attracted attention of practitioners as well as researchers. The main aim of IoT is to unify everything in world including things, people, place and process under a common infrastructure to provide information and control of state of objects around us. An attempt has been made in this paper to give an idea about IoT technology, opportunities and its future scope. IoT has brought significant change in the lives of people and in near future its impact on society will increase more and connected things in IoT will be much more than people. In near future, IoT will transform real world objects into intelligent virtual objects. The main objective of this paper is to present spectrum of possibilities of IoT and its future scope.
Logo Matching and Recognition for Avoiding Duplicate Logos

: Logo matching and recognition is mainly done in order to reveal duplicate logos which have a slight difference from the original logos in order to deceive customer. In this paper an effective logo matching and recognition method called Context-Dependent Similarity method is performed. Firstly dataset of logo images are created for the reference images, then another test image which have logos in it is taken as the input and start matching with the dataset logo images to check whether the input image is fake or genuine logo based on the dataset image. For this features of logos images for both the reference and test images are extracted and based on their extracted features matching is performed using Context-Dependent Similarity method.
Isolation and Geographical Diversity of Bacillus thuringiensis from Some Soils in Iran

Bacillus thuringiensis is a spore-forming bacterium showing the unusual ability to produce endogenous crystals during sporulation that are toxic for some pest insects. This work was performed to study the Isolation Bacillus genus and biochemical Identification of B. thuringiensis and it`s ecological distribution from some Iranian soils and also introducing soil as a strength source of this bacterium. Using a standard isolation method with specific medium, B. thuringiensis was isolated from 23 out of 30 soil samples collected in the Soil and Water Research Institute (SWRI) of Iran. The bacillus population percentage mean of samples` total bacteria population was (44.44%) and B.thuringiensis population percentage mean of total bacteria population was 3.45%. Maximum and minimum B.T. population logarithms were 4.78 and 0 for sample number 2759 and 7 samples had no B.T. population, respectively. Using Muller Hilton agar for total bacteria population and Hicrome Bacillus Agar for bacillus genus population and then biochemical Identification of bacillus isolates showed a great biodiversity among soil samples, which were distributed among different species, including megaterium, polymixa and cereus etc. We found variable percentages of B.thuringiensis isolates among soil samples and knew about soil as a valuable source of this bacterium to use in biological pesticides and insecticides because of their high ability against pests and insects. Keywords— Bacillus thuringiensis, Insecticides, Geographical diversity.
VEHICLE DETECTION BY IMAGE PROCESSING USING MATLAB: A COLOUR BASED APPROACH

- Due to increasing traffic in the modern times it is imperative to design a system effective in maintaining a record of vehicles passing through a lane or a road. This will help to decrease human interference with the system and result in avoidance of faulty data. Our method would try to focus on detecting cars based on color , so that a proper information about transiting vehicles can be maintained. With the development of color based tracking mechanism tracking of car will become more easier and will lead to further control over the vehicular accident. it has observed that drivers tend to get lethargic and lose focus in such scenarios lead to occurrences of accidents in modern times. hence our mechanism will help to predict the course of vehicle movement and lead to further help so that driver mishaps can be kept in check for road traffic safety and pedestrian protection in the lanes.
Prediction for Stock Marketing Using Machine Learning

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. This paper will showcase how to perform stock prediction using Machine Learning algorithms: Linear Regression, Random Forest and Multilayer Perceptron.
An Efficient Converse Mapping Technique in Modern Information Retrieval

— A traditional forward dictionary maps from words to their definitions. Unlike a regular dictionary, the reverse dictionary performs converse mapping that maps from definitions to words. The user input phrase describes the definition of desired concept, and returns an efficient candidate word that satisfies the input phrase. The reverse dictionary addresses the widespread problem of knowing the meaning of a word, but unable to recall the appropriate word on demand. The converse mapping technique finds the exact result for the user entered keyword by comparing the partitioned input with dictionary database. The partitioning method increases the overall scalability and distributes the data across multiple threads. The efficiency of the reverse dictionary can be improved by reducing the set of definitions in the comparison process. The query expansion technique is used to improve the potential of reverse dictionary and increases the probability of identifying relevant definition. The approaches of reverse mapping provide significant improvements in the performance scale. The converse mapping technique in modern information retrieval extracts the best matched result without sacrificing the quality of the solution.
Effect of Lactic Acid Bacteria against Heavy Metals Toxicity in Rats

Cadmium and lead are highly toxic metals; people are exposed to them primarily through food and water. Therefore the study aimed to estimate the effect of lactic acid bacteria against toxicity induced by contaminated diet with lead and cadmium mixture in rats. Forty two Albino male rats (Sprague Dowely strain) of an average weight 130 ± 10 g were divided into 6 groups each group contains 7 rats. G1: fed on basal diet (negative control); G2: fed on contaminated food with 0.025mg lead acetate/kg diet + 0.025mg cadmium chloride /kg diet (positive control); G3: fed on basal diet supplemented with strain 1 of lactic acid bacteria (Streptococcus thermophilus); G4: fed on basal diet supplemented with strain 2 of lactic acid bacteria (Lactobacillus bulgaricus). The other two groups received heavy metals contaminated diet supplemented with strain1and strain2 lactic acid bacteria for 6 weeks. The results revealed that positive control gave a highly significant increased in liver functions (alanine aminotransferase (ALT) and aspartate minotransferase (AST) activities), kidney functions (creatinine and urea); significantly decreased in glutathione peroxidase (GPX), blood hemoglobin, body weight and feed efficiency ratio. However lactic acid strains supplemented to heavy metals treated group significantly improved the in glutathione peroxydase, blood hemoglobin, body weight and feed efficiency ratio and the elevation of ALT, AST, creatinine and urea. The results also showed that the group received basal diet supplemented with strain 1 (Streptococcus thermophilus) and strain 2 (Lactobacillus bulgaricus) has beneficial health effects on animals. It was noticed that the group received strain 1 (Streptococcus thermophilus) showed better results than strain 2 (Lactobacillus bulgaricus). The results of histopathology obtained also indicate that tested lactic acid bacteria strains have an effective role against the toxicity induced by lead and cadmium. These results indicated the potential protective action of tested lactic acid strains against lead and cadmium toxicity as well as their beneficial health effects. This may be due the ability of lactic acid strains to bind heavy metals, the DNA protective effect of LAB and thought to have several presumably beneficial effects on immune function. In addition LAB decreased the amount of administered carcinogens reaching the blood. [Abou-Baker Salim, Ibrahim H. Badawy and Seham S. Kassem. Effect of Lactic Acid Bacteria against Heavy Metals Toxicity in Rats. Journal of American Science 2011;7(4):264-274]. (ISSN: 1545-1003). http://www.americanscience. org.
An Efficient Approach for Retrieving Personalized User Goals

--The most important facility of a search engine is to retrieve relevant information as early as possible. For this understanding user search goal is necessary. For the same query the user information need may be different. In this paper we propose a method to infer user search goal by analyzing search engine query logs. User search goals are discovered by clustering proposed feedback sessions. Feedback sessions are constructed from user click-through logs and it reflect information need of users. Then propose novel approach to generate pseudo-documents which represent feedback session for clustering. We present a large-scale evaluation framework for personalized search based on query logs and then evaluate five personalized search algorithms (including two click-based ones and three topical-interest-based ones). It represents a significant improvement over generic Web search for some queries, while it has little effect and even harms query performance under some situations.
Effect of processing on phytic acid content and nutrient availability in food grains

Nutrient paucity due to unavailability of quality food sources is a major impediment to the progress in improvement in the field of human nutrition. Phytic acid is a major anti nutritional factor that binds with cationic nutrients like zinc and iron, and makes them unavailable for human intestinal absorption. Zinc and iron are among the important nutrients required for human growth and development. This study was aimed to know the effect of cooking on nutrient availability with respect to relative phytic acid contents. Seeds of five different economically important food crops namely peanut, sunflower, soybean, pigeon pea and rice were used. Reduced phytic acid content was observed in cooked seeds of peanut (47 %), soybean (52 %), sunflower (56.5 %), pigeon pea (49.5 %) and rice (47.9 %). However, soybean and rice zinc contents and peanut, pigeon pea and rice iron contents were increased in cooked seeds. The mean nutrient availability in cooked and noncooked seeds was statistically non-significant (p < 0.05). The cooking treatment significantly (p < 0.05) reduced the inherent phytic acid content in seeds besides soaking and germination treatments, although the phytic acid break down did not show increased nutrients content as expected in all food crops.
Web Query Classification and URL Ranking Based On Click through Approach

― In a web based application; different users may have different search goals when they submit it to a search engine. For a broad-topic and ambiguous query it is difficult. Here we propose a novel approach to infer user search goals by analyzing search engine query logs. This is typically shown in cases such as these: Different users have different backgrounds and interests. However, effective personalization cannot be achieved without accurate user profiles. We propose a framework that enables large-scale evaluation of personalized search. The goal of personalized IR (information retrieval) is to return search results that better match the user intent. First, we propose a framework to discover different user search goals for a query by clustering the proposed feedback sessions. Feedback sessions are getting constructed from user click-through logs and can efficiently reflect the information needs of users. Second, we propose an approach to generate pseudo-documents to better represent the feedback sessions for clustering. Most document-based methods focus on analyzing users’ clicking and browsing behaviors recorded at the users’ clickthrough data. In the Web search engines, clickthrough data are important implicit feedback mechanism from users. The bolded documents that have been clicked by the user have been ranked. Several personalized systems that employ clickthrough data to capture users’ interest have been proposed.
An Energy Efficient Routing Protocol for WSN Assisting IoT

: In present modernized era Wireless Sensor Network (WSN) is used for many applications like Smart homes, Weather monitoring systems, Smart cities etc. and it is integrated into the (IoT). In this the nodes are resource strained in different ways, like energy resource, Storage resource, computing resource etc. To maintain a long network a powerful routing protocols are required. Here we proposed a technique for WSN using a routing protocol for energy efficient assisting IoT based on Hybrid optimization techniques to enhance the energy efficiency and network lifetime. A new series of hybrid algorithm is adapted for clusters and based on the center position cluster head(CH) which is rotated for distributing the energy between the sensor nodes. An advance technique is proposed for enhancing the network lifetime and energy utilization. A remaining energy is viewed in the proposed routing protocol in certain nodes to evaluate the center position. The proposed simulation result will show and compare with LEACH, LEACH-C, GEEC and the present existing EECRP. The proposed routing protocol will perform better than the existing system.
The impacts of agricultural firm ’ s power on farmers ’ trust and relationship commitment : Data from " a company + farmers " in China

The purpose of this study is to investigate the impact of agricultural firm’s five types of powers on farmers` trust and relationship commitment in "a company + farmers" organization. Based on data collected from 462 farmers in "contract-farming" schemes under Chinese agricultural industrialization framework, this study proposes and examines a model of "power trust, relationship commitment". The results show that trust has significantly positive influence on relationship commitment. Furthermore, different types of company’s powers influence farmers’ trust and relationship commitment differently. These findings can offer guidance for the development of agricultural industrialization in China.
Generating associations rule mining using Apriori and FPGrowth Algorithms

- Mining frequent itemsets from the large transactional database is one of the most challenging problems in data mining. In many real world scenarios, the data is not extracted from single data source but from distributed and heterogeneous ones. The discovered knowledge is expected to better business operations. In data mining methods association rule mining is one of the most popular one. However, mining informative patterns using association rules often results in a very large no of founding patterns, leaving the analyst with the task to go through all the rules and discover interesting ones In this paper we present a generating associations rules using Apriori and FPGrowth algorithms.
Dynamic Model of Forecasting Stock Prices

Fajrin Satria Dwi Kesumah, Ernie Hendrawaty, Mustofa Usman, Edwin Russel, Rialdi Azhar, Widiarti and Prayudha Ananta Department of Management, Faculty of Economics and Business, Department of Accounting, Faculty of Economics and Business, Department of Economics Development, Faculty of Economics and Business, Department of Mathematics, Faculty of Mathematics and Sciences, Universitas Lampung, Bandar Lampung, Indonesia